Randomly sampling reference ADC for calibration

ABSTRACT

Analog-to-digital converters (ADCs) can have errors which can affect their performance. To improve the performance, many techniques have been used to compensate or correct for the errors. When the ADCs are being implemented with sub-micron technology, ADCs can be readily and easily equipped with an on-chip microprocessor for performing a variety of digital functions. The on-chip microprocessor and any suitable digital circuitry can implement functions for reducing those errors, enabling certain undesirable artifacts to be reduced, and providing a flexible platform for a highly configurable ADC. The on-chip microprocessor is particularly useful for a randomized time-interleaved ADC. Moreover, a randomly sampling ADC can be added in parallel to a main ADC for calibration purposes. Furthermore, the overall system can include an efficient implementation for correcting errors in an ADC.

PRIORITY DATA

This patent application receives benefit from or claims priority to U.S.Provisional Application 62/093,391, entitled “DIGITALLY ASSISTEDTECHNIQUES FOR ANALOG-TO-DIGITAL CONVERTERS” filed on Dec. 17, 2014. Theprovisional application is incorporated by reference herein in itsentirety.

TECHNICAL FIELD OF THE DISCLOSURE

The present invention relates to the field of integrated circuits, inparticular to digitally assisted techniques usable for analog-to-digitalconverters.

BACKGROUND

In many electronics applications, an analog input signal is converted toa digital output signal (e.g., for further digital signal processing).For instance, in precision measurement systems, electronics are providedwith one or more sensors to make measurements, and these sensors maygenerate an analog signal. The analog signal would then be provided toan analog-to-digital converter (ADC) as input to generate a digitaloutput signal for further processing. In another instance, an antennagenerates an analog signal based on the electromagnetic waves carryinginformation/signals in the air. The analog signal generated by theantenna is then provided as input to an ADC to generate a digital outputsignal for further processing.

ADCs can be found in many places such as broadband communicationsystems, audio systems, receiver systems, etc. ADCs can translate analogelectrical signals representing real-world phenomenon, e.g., light,sound, temperature or pressure for data processing purposes. Designingan ADC is a non-trivial task because each application may have differentneeds in performance, power, cost and size. ADCs are used in a broadrange of applications including communications, energy, healthcare,instrumentation and measurement, motor and power control, industrialautomation and aerospace/defense. As the applications needing ADCs grow,the need for accurate and reliable conversion performance also grows.

Generally speaking ADCs are electronic devices that convert a continuousphysical quantity carried by an analog signal to a digital number thatrepresents the quantity's amplitude (or to a digital signal carryingthat digital number). An ADC is typically composed of many devicesmaking up an integrated circuit or a chip. An ADC is usually defined bythe following application requirements: its bandwidth (the range offrequencies of analog signals it can properly convert to a digitalsignal), its resolution (the number of discrete levels the maximumanalog signal can be divided into and represented in the digitalsignal), and its signal to noise ratio (how accurately the ADC canmeasure signal relative to the noise the ADC introduces). ADCs have manydifferent designs, which can be chosen based on the applicationrequirements. In many cases, it is not trivial to design an ADC thatmeets the application requirements while providing adequate performance.

Overview

Analog-to-digital converters (ADCs) can have errors which can affecttheir performance, in particular, their (effective) resolution. Speedand resolution is often a trade-off, where higher speed ADCs tend tohave lower resolution. As the speed of ADCs become faster, the need formeasures to compensate or correct for these errors is higher so that theADCs do not gain speed while losing resolution. To improve theperformance, many techniques have been used to compensate or correct forthe errors. When the ADCs are being implemented with sub-microntechnology, ADCs can be readily and easily equipped with an on-chipmicroprocessor for performing a variety of digital functions. Theon-chip microprocessor and any suitable digital circuitry can implementa wealth of functions for reducing those errors, enabling certainundesirable artifacts to be reduced, and providing a flexible platformfor a highly configurable ADC. The on-chip microprocessor isparticularly useful for a randomized time-interleaved ADC. Moreover, arandomly sampling ADC can be added in parallel to a main ADC (e.g.,randomized time-interleaved ADC) for calibration purposes. Furthermore,the overall system can include an efficient implementation forcorrecting errors in an ADC (e.g., a multi-stage ADC).

BRIEF DESCRIPTION OF THE DRAWINGS

To provide a more complete understanding of the present disclosure andfeatures and advantages thereof, reference is made to the followingdescription, taken in conjunction with the accompanying figures, whereinlike reference numerals represent like parts, in which:

FIG. 1 shows an exemplary successive-approximation ADC, according tosome embodiments of the disclosure;

FIG. 2 shows an exemplary internal DAC used for an SAR ADC, according tosome embodiments of the disclosure;

FIG. 3 shows an exemplary subranging ADC, according to some embodimentsof the disclosure;

FIG. 4 shows two exemplary pipelined ADCs, according to some embodimentsof the disclosure;

FIG. 5 shows an exemplary sigma-delta modulator, according to someembodiments of the disclosure;

FIG. 6 shows an exemplary second-order sigma-delta modulator, accordingto some embodiments of the disclosure;

FIG. 7A shows an exemplary time-interleaved ADC having two sub-ADCs, andFIG. 7B shows a timing diagram illustrating sampling edges for theexemplary time-interleaved ADC of FIG. 7A.

FIG. 8 shows an exemplary layout of a conventional ADC chip havingdedicated and specialized analog or digital processing circuitry;

FIG. 9 shows an exemplary layout of a ADC chip having an on-chipmicroprocessor, according to some embodiments of the disclosure;

FIG. 10 shows a system diagram having a converter and an on-chipmicroprocessor, according to some embodiments of the disclosure;

FIG. 11 shows a system diagram having a converter, an on-chipmicroprocessor, and clock generator(s), according to some embodiments ofthe disclosure;

FIG. 12 shows an exemplary stage of a pipeline ADC, according to someembodiments of the disclosure;

FIGS. 13-18 shows a series of exemplary voltage plots which illustratethe operation inside a pipeline ADC, and one or more possible errorsources, according to some embodiments of the disclosure;

FIG. 19 shows an exemplary pipeline ADC having 6 stages, equipped withdither injection, according to some embodiments of the disclosure;

FIG. 20 illustrates a correlation scheme usable for calibration,according to some embodiments of the disclosure;

FIG. 21 illustrates a gain error calibration scheme, according to someembodiments of the disclosure;

FIG. 22 illustrates another gain error calibration scheme, according tosome embodiments of the disclosure;

FIG. 23A-B show exemplary calibration functions suited for being carriedout by the on-chip uP, according to some embodiments of the disclosure;

FIG. 24 shows an exemplary system diagram of an exemplary interleavedADC having an on-chip uP, according to some embodiments of thedisclosure;

FIG. 25 shows an exemplary hardware flow for flash ADC calibration andpipeline stage calibration, according to some embodiments of thedisclosure;

FIG. 26 shows an exemplary hardware flow for dither subtraction andexemplary accumulation and decimation blocks, according to someembodiments of the disclosure;

FIG. 27 illustrates sampling of adjacent sub-ADCs, according to someembodiments of the disclosure;

FIG. 28 illustrates sampling of reference and adjacent sub-ADCs,according to some embodiments of the disclosure; and

FIG. 29 shows an exemplary on-chip uP and connections of the on-chip uPto communicate with the rest of the chip, according to some embodimentsof the disclosure.

DESCRIPTION OF EXAMPLE EMBODIMENTS OF THE DISCLOSURE

Understanding Analog-to-Digital Converters (ADCs)

There are many flavors of ADCs, each aiming to output a digitalrepresentation of the analog input provided to the ADC. The followingpassages discusses several of these flavors.

One example flavor of ADCs is the Successive Approximation Register ADC(SAR ADC). SAR ADCs are used often for data acquisition applications,especially where multiple channels are to be digitized. FIG. 1 shows anexemplary successive-approximation ADC, according to some embodiments ofthe disclosure. In one example, on the assertion of the CONVERTSTARTcommand the sample-and-hold (SHA) is placed in the hold mode, and allthe bits of the successive approximation register (SAR) are reset to “0”except the MSB which is set to “1”. The SAR output drives the internaldigital-to-analog converter (DAC). If the DAC output is greater than theanalog input, this bit in the SAR is reset, otherwise it is left set.The next most significant bit is then set to “1”. If the DAC output isgreater than the analog input, this bit in the SAR is reset, otherwiseit is left set. The process is repeated with each bit in turn. When allthe bits have been set, tested, and reset or not as appropriate, thecontents of the SAR correspond to the value of the analog input, and theconversion is complete. These bit “tests” can form the basis of a serialoutput version SAR-based ADC. Other algorithms besides this one can beused to generate the digital representation of the analog input. Theaccuracy of the SAR ADC can be affected by the accuracy of the internalDAC. FIG. 2 shows an exemplary internal DAC used for an SAR ADC,according to some embodiments of the disclosure. The exemplary internalDAC, shown using switched capacitor or charge redistribution techniques,can determine the overall accuracy and linearity of the SAR ADC. Evenwith precise lithography, matching of the capacitors is not alwaysperfect, and can degrade the performance of the SAR ADC if leftuntrimmed.

Another example flavor of ADCs is the pipelined ADC, which is typicallycategorized as a high speed ADC (e.g., with sample rates above 5 millionsamples per second (MSPS) or even above 10 MSPS). Pipelined ADCs areused often with video, sampling radio applications, instrumentation(digital oscilloscopes, digital spectrum analyzers), etc. Pipelined ADCshave their origins in subranging ADCs. FIG. 3 shows an exemplarysubranging ADC, according to some embodiments of the disclosure. Asillustrated by this example, a subranging ADC has two stages: a “coarse”conversion of N1 bits in the MSB sub-ADC (SADC), followed by a “fine”conversion of N2 bits in the LSB SADC. The N1-bit “coarse” conversion isconverted back to analog by an N1 bit sub-DAC (SDAC), and subtractedfrom the held analog signal and amplified to generate a residue signal.The residue signal is then applied to the N2 bit SADC. Typically, forthe subranging architecture to operate satisfactorily, both the N1 SADCand SDAC are better than N-bits accurate (N=N1+N2). The residue signaloffset and gain is adjusted such that it fills the range of the N2 SADCto avoid missing codes. Any non-linearity or drift in the N2 SADC wouldalso cause missing codes if it exceeds 1 LSB referenced to N-bits. Whenthe interstage alignment is not correct, missing codes would appear inthe overall ADC transfer function. To increase the speed of thesubranging ADC, pipelined ADCs are introduced. FIG. 4 shows twopipelined ADCs, according to some embodiments of the disclosure.Pipelined ADCs has a digitally corrected subranging architecture, inwhich each of the two stages operates on the data for one-half of theconversion cycle, and then passes its residue output to the next stagein the “pipeline” prior to the next phase of the sampling clock. In thetop drawing (A), two pipelined stages use an interstage track and hold(T/H) to provide interstage gain and give each stage some amount of timeto process the signal at is input. The interstage T/H serves as ananalog delay line—it is timed to enter the hold mode when thefirst-stage conversion is complete. This allows more settling time forthe internal SADCs, SDACs, and amplifiers, and allows the pipelinedconverter to operate at a much higher overall sampling rate than anon-pipelined version. The term “pipelined” refers to the ability of onestage to process data from the previous stage during any given clockcycle. At the end of each phase of a particular clock cycle, the outputof a given stage is passed on to the next stage using the T/H functionsand new data is shifted into the stage. The digital outputs of all butthe last stage in the “pipeline” can be stored in the appropriate numberof shift registers so that the digital data arriving at the correctionlogic corresponds to the same sample. In the bottom drawing (B), analternative architecture, a multiplying DAC is used to provide theappropriate amount of interstage gain as well as the subtractionfunction. In pipelined ADCs, phases of the clocks to the T/H amplifiersare important for achieving desired performance. It is understood by oneskilled in the art that there are many different implementations ordesigns for a pipelined ADC. For instance, some pipelined ADCs usesflash converters as building blocks, but some ADCs utilize otherarchitectures for the individual ADCs. Flash converters make use ofparallel comparators each operating at a slightly different referencevoltage determined by a resistor ladder network.

Yet another flavor of ADCs is the sigma-delta ADC, which is often usedin precision industrial measurement, voiceband, and audio applicationspace. The concepts used in sigma-delta ADCs are oversampling, noiseshaping, digital filtering, and decimation. In a noise spectrum fortraditional “Nyquist” operation, where the ADC input signal fallsbetween dc and f_(S/)2, and the quantization noise is uniformly spreadover the same bandwidth. The process of oversampling, followed bydigital filtering and decimation, increases the signal-to-noise ratio(SNR) within the Nyquist bandwidth (dc-to-ƒ_(S/)2 region). Moreover,when a sigma-delta modulator is used, the quantization noise can beshaped such that most of it occurs outside the bandwidth of interest,thereby further increasing the SNR in the dc-to-ƒ_(S/)2 region. FIG. 5shows an exemplary sigma-delta modulator, according to some embodimentsof the disclosure. The exemplary modulator includes a 1-bit ADC (e.g., acomparator) and a 1-bit DAC (e.g., a switch). Although there are anumber of multibit sigma-delta ADCs, those using the single-bitmodulator have the advantage of inherently excellent differentiallinearity. The output of the modulator is a 1-bit stream of data. Themodulator can accomplish the noise-shaping function by acting as alow-pass filter for the signal and a high-pass filter for thequantization noise. Although the simple first-order single-bit Σ-Δ ADCis inherently linear and monotonic because of the 1-bit ADC and 1-bitDAC, it does not provide sufficient noise shaping for high-resolutionapplications. Increasing the number of integrators in the modulator(similar to adding poles to a filter) provides more noise shaping at theexpense of a more complex design. FIG. 6 shows an exemplary second-ordersigma-delta modulator, according to some embodiments of the disclosure.Besides showing the architecture, the figure also shows the improvementin the noise shaping characteristic compared to a first-order modulator.Higher-order modulators (greater than third order) are difficult tostabilize and present significant design challenges.

Yet a further flavor of ADCs is the time-interleaved ADC, where an ADChas M multiple sub-ADCs (of any suitable architecture), which arerunning at a sample rate of 1/M of the overall system sample rate. Theresult drastically increases to increase the sample rate of the overallADC. Many (low-speed) ADCs can be used in parallel, operating insequence in a time-interleaved fashion, using appropriate clocking toincrease the effective combined ADC sampling rate. FIG. 7A shows anexemplary time-interleaved ADC having two sub-ADCs, and FIG. 7B shows atiming diagram illustrating sampling edges for the exemplarytime-interleaved ADC of FIG. 7A. In particular, FIG. 7A shows an exampleof a time-interleaved ADC having two sub-ADCs, ADC_0 and ADC_1, eachable to produce Y million samples per second (MS/s). Together, withappropriate clocking shown in FIG. 7B, the two sub-ADCs can provide anoverall sampling rate up to 2×Y MS/s. The appropriate clocking can beprovided by clock generator (“clock gen” block) to produce clock signalsor selection signals, q₀ and q₁, having different phases, to alternatelyselect a sub-ADC for converting the analog input signal to a digitaloutput. Referring back to FIG. 7A, the two sub-ADCs, ADC_0 and ADC_1,alternately (i.e., in sequential order or according to a fixed sequence)sample the input signal v_(in) and produce corresponding digitaloutputs, D_(out0) and D_(out1) respectively, which are then combined bythe digital combiner (“dig combiner” block) to produce the Y MS/sdigital output D_(out). In this example, the sub-ADCs operate accordingto a fixed sequence of [ . . . ADC_0, ADC_1, ADC_0, ADC_1, ADC_0, ADC_1,. . . ], e.g., in a round-robin fashion. A time-interleaved ADC havingtwo sub-ADC is described herein as an example for understanding theoperations of a time-interleaved ADC, and is not intended to be limitingto the disclosure. Other time-interleaved ADCs having more than twosub-ADCs are envisioned by the disclosure. Furthermore, time-interleavedADCs having three or more sub-ADCs can operate in a fixed sequence, arandomized sequence, or a pseudo-randomized sequence.

Two or more ADCs can sample, interleaved in time according to arandomized sequence or a pseudo-randomized sequence, the analog input.In such an example, the ADCs can be built fast enough that having aslittle as two ADCs can sample the analog input in a randomized sequence.In some embodiments, three or more ADCs can sample, interleaved in timeaccording to a randomized sequence or pseudo-randomized sequence. Insuch an example, one or more of the three or more ADCs may be “busy”,while two or more ones of the three or more ADCs may be “idle” (waitingto be selected/used). When the next sample is to be made, one of the“idle” ADCs can be selected at random from the ones which are “idle” totake the next sample in the pseudo-randomized sequence.

Yet another flavor of ADCs are multi-stage ADCs comprising multiplestages of analog-to-digital conversion, or multiple ADCs in cascade.Each stage generally includes an ADC. Stages can use the same ordifferent ADC architectures to resolve different parts of digital outputcode. Typically, a first analog-to-digital conversion stage resolves themost significant bit(s) based on the analog input and generates anoutput for the second (following the first) analog-to-digital conversionstage. The output can be a residue representing the difference betweenthe analog input and the digital output generated by a particular stage(i.e., the value of the most significant bit(s) resolved by the firststage). The second analog-to-digital conversion stage then performsanalog-to-digital conversion on the residue signal to resolve furtherbit(s) of the digital output. The second stage can generate a furtherresidue signal for following stage(s) of the multi-stage ADC. In somecases, a successive approximation register ADC can be considered amulti-stage ADC (e.g., if a segmented design is implemented to resolvethe most significant bits using a simple ADC and further bits areresolved by a SAR charge distribution architecture). Residue type ADCsincluding two-step ADCs, algorithmic ADCs, and pipeline ADCs are alsoconsidered as multi-stage ADCs. While the algorithmic ADCs can reuse asingle stage, each phase the single ADC is being reused can beconsidered a stage in the multi-stage ADC. Another form of multi-stageADCs is a multi-stage noise shaping sigma-delta (MASH) ADC, comprisingmultiple stages of delta-sigma ADCs or a combination of other type(s) ofADCs (e.g., flash ADC) and delta-sigma ADC(s).

The above-described ADC architectures are not intended to be limiting tothe disclosure. One skilled in the art that other architectures areenvisioned by the present disclosure.

Errors and Artifacts of ADCs

Although circuit designers aim to design and fabricate the perfect ADC,the circuitry of resulting ADC are often not perfect, or may not operateexactly as intended due to limitations in fabrication. Sometimes thecircuitry's behavior may also deviate from intended or desirablebehavior due to changes in operating conditions such as temperature, andaging of the substrate. These deviations can often lead to ADCs havingundesirable errors and artifacts. For SAR ADCs, the one common source oferror is the mismatches of the capacitors of the internal DAC. Fordelta-sigma ADCs, sources of error include offset errors, gain errors,and linearity errors. For pipelined ADCs, the sources of error includecomparator offset errors, reference voltage errors, phases of the clocksfed to the interstage T/H, thermal noise, sampling clock jitter,capacitor mismatch, interstage gain stage error, gain stage offset,interstage gain non-linearity, sub-ADC errors, sub-DAC errors, etc. Forinterleaved ADCs, sources of error for the individual sub-ADCs arepresent, as well as mismatches between the sub-ADCs in gain, offset,timing, bandwidth can exist.

Introduction of Microprocessors on-chip with ADCs

In conventional ADCs, dedicated and specialized analog and/or digitalcircuitry are provided on-chip or off-chip with the ADCs to measure,compensate and/or correct these errors. In some cases, the dedicated andspecialized analog or digital circuitry can perform pre-/post processingof signals. FIG. 8 shows an exemplary layout of a conventional ADC chiphaving dedicated and specialized analog or digital processing circuitry.It can be seen from the illustrative chip area layout of a chip 800 hasan ADC 802 area, an analog/digital logic 804 area for calibration(“cal”) and/or pre-/post-processing of signals, an optional memory 806area for storing output digital data, and a clock generator 808 (“clockgen”) area for generating clock signals. Providing these dedicated andspecialized analog or digital logic can add significant complexity anddesign time. Also, the circuitry is fixed without considerableconfigurability.

FIG. 9 shows an exemplary layout of an improved ADC chip having anon-chip microprocessor, according to some embodiments of the disclosure.It can be seen from the illustrative chip area layout of a chip 900 hasan ADC 902 area, an analog/digital logic 904 area for performing partsof calibration and/or pre-/post-processing of signals, an on-chipmicroprocessor (uP) 910 area for performing at least some parts ofcalibration and/or pre-/post-processing of signals, a memory 908 areafor storing data and/or instructions executable by the uP 910, and aclock generator 906 (“clock gen”) area for generating clock signals.

Within the context of the present disclosure, the on-chip uP (e.g.,on-chip uP 910) generally include circuitry that can perform functionsof a processing unit, or a central processing unit. The on-chip uP caninclude one or more arithmetic and logic unit (ALUs) as computationunits, which can perform operations such as addition, subtraction,multiplication, AND, OR, XOR, etc. The on-chip uP can include a registerfile or some form of memory for storing states, data, etc. The on-chipuP can include a control logic section which can retrieve instructionoperation codes from memory, and initiates a sequence of operations tobe executed by one or more ALUs. The on-chip uP can include interfacesfor accessing data and/or instructions from other parts of the chip,e.g., such as data from the ADC. The on-chip uP can include interfacesfor writing data in other parts of the chip as well. The on-chip uP mayinclude one or more interrupts that the ADC or any specialized circuitrycan use to wake up the on-chip uP and/or trigger particular function(s)of the on-chip uP.

One important advantage of providing an on-chip uP is the flexibilitythat the uP can provide over the conventional ADC (e.g., such as the oneshown in FIG. 8). Another important advantage is that an on-chip uP hasa set of computation units readily available for performing parts ofcalibration and/or pre-/post-processing of signals, making the on-chipuP highly suitable for providing digital functions for assisting theADC. The uP being on-chip can also communicate with the ADC in a muchfaster manner than an off-chip uP. The uP also lends itself easily toaccommodate an architecture where the on-chip uP can act as the centralcontroller for digitally controlling various parts of the chip,including the ADC and the digital/analog logic. For instance, the uP canbe used to address failure mechanisms (phased locked loop locks, out ofrange conditions, etc.) of an ADC system. In some embodiments, the uPcan perform control-like functions which can advantageously controlclocking/sampling of the ADC to limit spurious emissions of the ADC (orany suitable system).

Flexibility of on-chip Microprocessor

Without having to rely on dedicated and specialized circuitry fixedon-chip, the on-chip uP can be configured to execute any suitableinstructions to perform desired operations. This provides the technicaladvantage of being able to provide one chip which can adapt to manyapplications having different sets of requirements. Generally speaking,the on-chip uP is provided on the same semiconductor substrate as theADC itself. The on-chip uP can provide different levels ofconfigurability without requiring silicon changes. In some cases, theon-chip uP can be pre-loaded with different chunks of code designed fordifferent applications in, e.g., non-volatile memory (NVM), read-onlymemory (ROM). Fuses can be used to provide a (one-time) selection of thedesired chunk(s) of code to be executed by the uP, e.g., after tape-out,at the factory before the chip is delivered to the customer, or at thecustomer site prior to using the chip. One or more signals or pins canalso be used to select (once or multiple times) the desired chunk(s) ofcode to be executed by the uP. In some embodiments, an interface canalso be provided to allow a user of the chip to load one or more chunksof code onto (volatile) memory to be executed by the uP. Effectively,the functions being performed by the uP for assisting the ADC can bechanged or upgraded without silicon changes. This advantage can beuseful for updating or changing the calibration algorithms beingperformed, the operations of the digital/analog logic, and/or operationsperformed for pre-/post processing of signals. The configurability ofthe on-chip uP, and its accompanying on-chip memory also allowsdifferent parameters and/or variables to be set/configured/updated ondemand, e.g., to accommodate different operating conditions, differentenvironments of the chip (over time), and different applicationrequirements.

Broadly speaking, an interface to the uP can allow characteristics orparameters of the ADC to be changed. For instance, the interface to theuP can configure the ADC to run in different modes of operation (e.g.,test mode, high power mode, low power mode, high performance mode, lowperformance mode, high frequency mode, low frequency mode, etc.). Theinterface to the uP can also allow configuration of the ADC to turn onor off certain channels within the ADC, change the resolution of theADC, adjust the dynamic range of the ADC, etc. Furthermore, theinterface to the uP can enable certain functions such as the logging oferrors, abnormal events, etc. and access to on-chip or off-chip memorycan access the logs. In some cases, the interface to the uP can allowusers to select one or more presets of functions and/or parameters forcertain applications.

Techniques for calibration are evolving as the resolution for converterscontinue to grow higher and/or the speed for converters continue to growfaster. For instance, previous techniques applied to 6-bit or 8-bitconverter is less likely to be applicable to 12-bit, 14-bit, 16-bit,18-bit (or more) converters. Some of the calibration functions describedherein can address issue of increasing requirements, which may lead tocalibration functions which are more sophisticated or specialized fordifferent applications. For this reason, having a flexible platform forconfiguring calibration to meet different sets of applicationrequirements can be particularly advantageous. For instance, specializedcalibration functions can be selectively applied to push the performancehigher depending on the application.

Moving Towards More Digital Processing as Technology Nodes Get Smaller

Generally speaking, many conventional architectures implementcalibration functions using specialized analog hardware instead of usingan on-chip uP, or the architectures implement specialized digitalhardware instead of using an on-chip uP. There can be several tradeoffsbetween implementing functions using specialized circuitry versusimplementing functions using the on-chip uP. In one example, specializedcircuitry can be faster and consumes less power than an on-chip uP. Inanother example, specialized circuitry can take up less area on-chipthan providing an on-chip uP. In yet another example, specializedcircuitry is fixed is far less configurable than functions executable byan on-chip uP. In yet a further example, the computation blocks in an uPare “ready-to-use” (i.e., already designed), thus can be consideredeasier to implement than having to design the specialized circuitry forimplementing the same computation blocks. In yet an even furtherexample, some types of functions (e.g., mathematical computations,control functions) can be easier to implement using the internal digitallogic of an uP than having to implement those functions with specializedcircuitry.

As the technology nodes of Complementary metal-oxide-semiconductor(CMOS) process technology become smaller, digital correction andprocessing becomes cheaper. One reason for moving towards digitalcorrection, and go as far to provide an on-chip uP, is that the digitalprocessing gets cheaper in area and power relative to analog processing.For this reason, converters leverage digital post processing, e.g.,record what data outputs, and run digital multiply to correct it,without significant costs in power and area. Before, doing multiply withspecialized digital circuitry would have been very power hungry andlarge in area 180 nm node. However, in 28 nm technology node, digitalprocessing is far cheaper. Digital processing using an on-chip uP, asexplained herein, can be more adaptive and flexible too. It is importantto note that it is harder to do better analog processing for convertersin deep submicron nodes, which can demand more (digital) correction andprocessing. For these reasons, performing digital correction and/orprocessing using an on-chip uP provides significant technical advantagesover any power or cost increases for providing an on-chip uP.

The Interface Between Specialized Circuitry and the on-Chip uP

FIG. 10 shows a system diagram having a converter and an on-chipmicroprocessor, according to some embodiments of the disclosure. Thesystem 1000 shows a converter 1002. In this example, for purposes ofillustration, the converter 1002 include one ADC, or a plurality ofsub-ADCs (illustrated as a plurality of layers). For at least one ormore of the ADCs, the converter 1002 can include conversion circuitry1004 for making a conversion of the input signal IN to generate anoutput signal OUT. The ADC part 1004 can be coupled to calibrationcircuitry 1006 which can correct the signal in the digital domain,and/or compensate for errors in some part of the signal chain of theconversion circuitry 1004, e.g., in the analog domain. For someembodiments, the system 1000 further includes a reference converter 1003(the converter 1002 would then be considered as the main converter). Inthis example, the reference converter 1003 which can include referenceconversion circuitry 1020 and optionally reference calibration circuitry1022. Generally, the reference converter 1003 provides an additionalsignal path (converting IN alongside with converter 1002), which canserve as a reference for the calibration algorithms. Further toconverter 1002, an on-chip uP 1008 is provided to implement one or morefunctions assisting and/or controlling the system. For instance, theon-chip uP 1008 can implement adaptation/training algorithms forcalibrating converter 1002.

In many high speed applications, the converter 1002 is operating at avery fast rate (e.g., gigahertz) when compared with the on-chip uP 1008(e.g., megahertz). For this reason, high speed specialized circuitry canbe provided to provide measurements at a slower rate for the on-chip uP1008. The slower rate of the measurements can be programmable oradjusted on the fly as well. To accommodate the slower on-chip uP 1008,measured data of the converter 1002 can be recorded by specializedcircuitry 1010. Specialized circuitry 1010 can writing the measured datain a memory 1012, and the recording of the measured data is typicallynot performed by the on-chip uP 1008. The specialized circuitry 1010 canserve as an interface between the converter 1002 and the on-chip uP1008. The specialized circuitry 1010 can include analog circuitry,digital circuitry, or both. The measured data of the converter 1002 can,once recorded, be accessed by the on-chip uP 1008 at a reduced rate. Theon-chip uP 1008 can poll the memory 1012 for measured data, or thespecialized circuitry 1010 can send an interrupt to the on-chip uP 1008.The on-chip uP 1008 can read the measurement data from the memory 1012,and perform any suitable algorithm(s) which can update the statevariables for the calibration algorithms to generate coefficient(s)which can be used to calibrate the ADC, or used by specialized circuitry1010 for compensating and/or correction of errors. The coefficient(s)can be written (by the on-chip uP 1008 or the specialized circuitry1010) to memory elements that are accessible by the converter 1002 orthe specialized circuitry 1010 to compensate and/or correct errors. Theon-chip uP 1008 can write coefficient(s) to one or more of thefollowing: register(s) accessible by the conversion circuitry 1004,register(s) accessible by the calibration circuitry 1006, andregister(s) accessible by the reference ADC 1003. If multiple channels(sub-ADCs for example) are used, any one or more of the channels caninclude its own set of associated register(s) to which the on-chip uP1008 can write coefficient(s). These register(s) can be accessible bythe respective conversion circuitry and/or calibration circuitry.

On-chip uP as an Adaptation or Training Engine

The slower speed of the uP lends itself to performing functions wherethe speed of the functions and processing do not need to run at the rateof the ADC. For instance, the uP can be used to implement an adaptationor training engine. The ADC can be provisioned with a set ofpredetermined coefficients (e.g., via factory calibration), and the uPcan run an adaptation or training algorithm that can update thecoefficients during the lifetime of the device. Typically suchadaptation or training algorithm is preferably running at a slower speedthan the ADC to avoid reacting too quickly to aberrant conditions.Adaptation or training algorithms can also be computationally complex,but can be readily implemented using the ALU(s) of the on-chip uP.

Implementing adaptation or training algorithm is not trivial.Preferably, the algorithm should not change the coefficients of thesystem towards an undesirable direction under certain pathologicalcondition. For this reason, the adaptation or training algorithm ispreferably agile, and easily adaptable. Implementing the algorithm usingthe flexible platform of the uP can help provide such agility andadaptability. Many conventional adaptation or training algorithm canassume there is a lot of activity in the input signal, and theconventional algorithm could potentially wander off if there is noactivity for a period of time. One function the uP can advantageouslyprovide is the ability to detect certain conditions in the input orother parts of the ADC so that the adaptation or training algorithm canadjust appropriately (adjust or tune certain variables or adaptationrates of the algorithm, or turn on or off at least part of thealgorithm, shift to use different algorithm(s), etc.) based on thoseconditions. For instance, the uP can adapt based on small signals versuslarge signals, low frequency versus high frequency, lots of activityversus no or very little activity, etc. In some cases, specializedcircuitry can be provided to detect such conditions, or a reference ADCcan be used to get an objective view of the input signal or inferconditions of the ADC. Such flexibility can allow the ADC to operateover a wide range of conditions or types of input signals with rangingcharacteristics, statistics, or signature.

Taxonomy of Calibration and Digitally Assisted Functions

Many functions related to an ADC, e.g., calibration,pre-/post-processing, can be performed at least in part by the on-chipuP and/or specialized circuitry (typically digital circuitry, but caninclude mixed-signal circuitry). The present disclosure describes avariety of these functions, and the on-chip uP or specialized digitalcircuitry can provide any one or more of the functions to meet or exceedthe application requirements. It is envisioned by the disclosure thatmany of the functions can cooperate or be provided in combination.

To better understand the functions that can be performed by on-chip uPor specialized digital circuitry, the following table illustrates someof the taxonomy which can be used to describe the varying functions.

The following taxonomy is meant to be illustrative and not limiting: Howis the uP or Digitally-assisted clocking, where digital circuitry can beused to specialized control clocking and sampling (e.g., assist ingenerating the desired digital circuitry clock signals) performing theCalibration, where the on-chip uP can be used to perform some function?operations for determining one or more errors, and/or computing errorcoefficients which can be used to compensate for the error in the analogdomain or correct for the error in the digital domain. Pre-processing ofanalog input signals to the ADC, where the on- chip uP can controlcircuitry that improves/conditions the input signal prior to conversionAdjust the converter signal chain, where the on-chip uP can configurethe converter signal chain to adjust or fix the signal chainPost-processing of digital output signals of the ADC, where the on- chipuP can control digital circuitry to improve the output signal afterconversion or perform the digital post-processing itself What is the on-Noise chip uP or Undesirable spurs in the spectrum specialized Staticerrors digital circuitry Dynamic errors (e.g., amplifier distortions)attempting to fix Aging effects or what issue Mismatches betweenchannels, e.g., interleaved channels are the uP or Input, or inputfrequency dependent distortions specialized Clocking issues digitalcircuitry Linearity issues (integral non-linearity, dynamicnon-linearity) trying to Offset errors address? Gain errors Quadratureerror correction Digital pre-distortion Sample-order dependent effects(e.g., for randomized interleaved ADCs) (many other types of errors areenvisioned by the disclosure) What is the Capacitor correction in DACsfeature provided “Large” dither injections for the multiplying DAC(MDAC) and or enabled by (flash ADC) of stage in a pipeline converteron-chip uP or “Small” dither injections for the MDAC specializedInterstage gain error (IGE) calibration digital circuitry Interstagememory error (IME) calibration related to a situation where a presentsample is influenced by a past sample Kickback calibration (e.g., stage1 of a pipeline ADC kicking back to input of a pipeline ADC whencapacitors are switched back onto the input) Interleaving gaincorrection Interleaving DC correction Interleaving timing correctionInterleaving bandwidth correction Sample order dependent errorcorrection (caused by sub-ADCs that took previous samples interferingwith one another) Flash/MDAC timing skew or delay trimming Comparatortrimming/Flash ADC comparator offsets (Flash) ADC/MDAC mismatch errorcorrection Buffer/Sampler NLC When is the on- When device is in thefactory (e.g., devices are trimmed using chip uP or fuses and/ornon-volatile memory, before the converter is shipped specialized to thecustomer) digital circuitry Foreground (e.g., at start up or power up,offline with test vectors) performing its Background (e.g., continually,or without the converter being function? taken offline) In-situcalibration (e.g., injecting a signal that makes its way into the signalchain to fix parts of the system) Self-calibration (e.g., calibrationwith or without being triggered by a user or external inputs) System(sys) trim/calibration (e.g., providing an interface to the on-chip uPto allow a user to access to controls and/or algorithms that cancalibrate devices the chip either in the foreground or background,and/or provide signal hookups (allowing a user to provide a desiredinput) that can better inform the training/adaptation algorithms forcalibration) A combination of any one or more of the above (e.g.,perform factory calibration and store parameters in non-volatile memoryand perform foreground and/or background to update parameters involatile memory or revert back to factory parameters)

Spread Spectrum Clocking or Sampling for the uP and/or the ADC

FIG. 11 shows a system diagram having a converter, an on-chipmicroprocessor, and clock generator(s), according to some embodiments ofthe disclosure. The system 1100 shows a (main) converter 1002. In thisexample, for purposes of illustration, the converter 1002 include one ormore channels (e.g., one ADC, or a plurality of sub-ADCs) for making aconversion of the input signal IN to generate an output signal OUT. Forsome embodiments, the system 1100 further includes a reference converter1003 (the converter 1002 would then be considered as the mainconverter). The reference ADC 1020 provides an additional signal path(converting IN alongside with converter 1002), which can serve as areference for the calibration algorithms. Further to converter 1002, anon-chip uP 1008 is provided to implement one or more functions assistingand/or controlling the system. For instance, the on-chip uP 1008 canimplement adaptation/training algorithms for calibrating converter 1002.

The system 1100 is a complex, mixed-signal system. Also, the rates forthe converter 1002, reference converter 1003, and on-chip uP 1008 canvary. For instance, the on-chip uP 1008 can run at a rate that issignificantly slower than the converter 1002. The reference converter1003 can sample the input signal IN at the same rate as the converter1002. In some cases, the reference converter 1003 can sample the inputsignal IN at a different rate from the converter 1002, and/or at adifferent rate than the interleaved channels of the converter 1002.

One issue of such high performance mixed-signal chip is that digitalcircuitry tends to clock the circuitry at one or a small set offrequencies. There is usually a lot of energy at or near thosefrequencies. That can couple into the analog circuitry, and create tonesat or near those frequencies or other undesirable frequency locations,thereby limiting performance. To address this concern, it is possible toapply randomization to the clock signals of the system, i.e., providespread spectrum clocking. Randomization can help spread some of thetones into the noise floor. The clock signal can on average a particularfrequency, but instantaneous period of the clock changes or israndomized.

The solution can include one or more of the following: providing a clockgenerator 1106 for spread spectrum clocking of the on-chip uP 1008,providing a clock generator 1108 for spread spectrum clocking of the(main) converter 1002 (and any interleaved channels therein) and/or thereference converter 1003. To generate the clock, clock generator 1106and clock generator 1108 can include specialized digital circuitry. Thespecialized digital circuitry can include one or more clock dividercircuits that can output an edge in the output signal for every X numberof cycles of the input clock, and a randomization engine that canrandomize X.

One embodiment includes providing spread spectrum clocking of theon-chip uP 1008. For instance, the clock generator 1106 can beconfigured to generate clock signals that run the on-chip uP 1008 at 100MHz on average, but the clock signal's instantaneous frequency can rangefrom 75 MHz to 125 MHz. Phrased differently, the period of the clocksignal waveform over time varies, but on average stay around 100 MHz.Advantageously, the spectrum contribution or energy from the clock ofthe on-chip uP 1008 is spread over 75-125 MHz, and the amount of energyat any one frequency is greatly reduced by spread spectrum clocking ofthe on-chip uP 1008. Even if the energy couples back into the analogcircuitry, it is generally below the noise floor of the overall system1100 (i.e., the converter 1002).

Besides providing spread spectrum clocking for the on-chip uP 1008,spread spectrum clocking can also be used for the converter 1002 and/orreference converter 1003, where the clock signal(s) generated by clockgenerator 1108 can run the converter(s) at a desired frequency onaverage, but any instantaneous frequency of the clock signal can varyover time (having a range of clock periods). For instance, the clocksignal periods can be randomized to cause the converters to sample theinput signal according to randomized periods to avoid pure periodicityin the sampling systems.

Going even further, clocking of time-interleaved ADCs can alsorandomized, i.e., the order sequence or sampling sequence of thetime-interleaved sub-ADCs, to further randomize the overall system. Insome cases, normal interleaving (sequential interleaving withoutrandomized sequence or order), certain input frequencies can causetraining and/or adaptation algorithms to diverge if the input frequencyis at the same frequency as the clocking frequency of the sub-ADCs. Thesequential (non-randomized sampling) appears as a DC offset to each ofthe converters, there is no information of the gain or timing in thesignal. If an algorithm attempts to try to calibrate on that signal, thealgorithm will diverge and the part will cease to work.

Broadly speaking, randomization in clocking makes the system 1100 morerobust and tolerant of different types of input signals when compared tosystems without randomization of the clocks. Furthermore, randomizationcan help average out errors, or make the errors less significant,especially for errors that aren't easily corrected by other means.Spread spectrum clocking effectively help alleviate issues with signalsthat are harmonically related to the clock from aliasing and causingissues, e.g., Fs/2, Fs/4, Fs/8, etc (Fs=sampling frequency), For Fs/8with 8 sequentially interleaved ADCs each sub-ADC would have a DC input,etc.

Understanding Errors in Pipeline ADCs: Gain Error and DAC Error

Some converters include a main converter that is a pipeline ADCs. Thepresent disclosure describes how some of the errors in the pipeline ADCcan be corrected with the assistance from specialized digital circuitryand/or the on-chip uP. Usually, a pipeline ADC includes a plurality ofstages (as previously explained in relation to FIG. 4), where each stageincludes a multiplying DAC (MDAC). FIG. 12 shows an exemplary stage of apipeline ADC, according to some embodiments of the disclosure. Theexemplary stage can include ADC 1204, and MDAC 1202. The ADC 1204 canconvert an input, e.g., Vin, into a digital output. Examples of the ADC1205 include a flash ADC, 2-bit ADC, 3-bit ADC, 4-bit ADC, and anysuitable low resolution ADC. The ADC 1204 may include a plurality ofcomparators that compare the input Vin against a plurality of differentreference voltages, and accordingly, generate a digital output (e.g., anoutput code) representative of the input Vin. The digital output is fedto DAC 1206 such that the digital output is converted back into ananalog signal Vin′. The summation/difference node 1208 finds thedifference between Vin and Vin′, and the difference is increased in gainby residue amplifier 1210 to generate output Vout (e.g., residue for thenext stage of the pipeline ADC). In this example, the gain is 4.However, other amounts of gain are possible. The ADC 1204 can be a2-bit, 3-bit, or 4-bit converter, and usually has some quantizationerror. However, the setup of the MDAC 1202 reduces the voltage swing ofthe input to the residue amplifier 1210 (Vin-Vin′). Each stage cangenerate a number of bits, which can then be combined to generate adigital output for the overall pipeline ADC.

The MDAC 1202 can include sample and hold circuitry (not shown), DAC1206, summation/difference node 1208, and the residue amplifier 1210.The MDAC 1202 can be implemented as a single switched-capacitor circuitblock. The MDAC 1202, is typically not perfect, and can exhibit one ormore errors. These errors can be calibrated or mitigated through thehelp of the specialized digital circuitry and/or the on-chip uP throughone or more digitally assisted functions. FIGS. 13-18 shows a series ofexemplary voltage plots which illustrate the operation inside a pipelineADC or a stage of the pipeline ADC, and one or more possible errorsources, according to some embodiments of the disclosure.

Referring to FIG. 13, a virtual (or ideal) transfer function of an MDACis shown with an exemplary gain of 4 (e.g., Vout=4*Vin). Generallyspeaking, as the input increases, the output would increase with acorresponding amount. It can be seen that with DAC subtraction (i.e.,the subtraction which generates Vin-Vin′), residue Vout can be limitedto a reasonable range of voltages suitable for the next stage, asillustrated by the ideal waveform of the residue Vout. More often thannot, the ADC in the pipeline stage (e.g., ADC 1204 of FIG. 12) is notideal. For instance, the comparators in the ADC can have an offset,which could lead to the residue Vout having imperfect steps. Referringto FIG. 14, the waveform of residue Vout is shown, where a comparatoroffset is present. The residue Vout can overshoot or undershoot at theADC thresholds due to comparator offsets. Generally speaking, trimmingat test or during calibration can reduce the comparator offset, so thatthe error does not go beyond a reasonable range limited by the inputrange of the following stage. The trimming (e.g., involving fuses,non-volatile memory) and measurements of the output can be performed byspecialized digital circuitry, and the specialized digital circuitry canstore the measurements in a memory that is accessible by the on-chip uPfor calibration. In some cases, the on-chip uP and/or the specializeddigital circuitry can perform the trimming once error coefficients aredetermined based on the measurements. If the error gets too large andgoes beyond the reasonable range, the system can have catastrophicissues. This concern is even more significant in smaller technologynodes where the range of acceptable voltages is far smaller.

When a plurality of stages are pipelined together for the ADC, theresults from each stage are combined or reconstructed to produce a(close to ideal) digital output that is representative of the originalinput Vin. FIG. 15 shows the residue Vout of a first stage (“STAGE 1RESIDUE Vout”) and the residue Vout of a second stage (“STAGE 2 RESIDUEVout”) and the reconstructed digital output (represented as an analogsignal for illustration, and shown as “STAGE 1+STAGE 2 DIGITAL OUTPUT”).The reconstructed digital output of FIG. 15 appears close to the virtualtransfer function shown in FIG. 13. To provide better performance of theoverall pipeline ADC, a designer can improve the accuracy of theindividual stages by addressing one or more sources of error present inthe individual stages.

One source of error in the individual stages is the gain error, and theeffect of an exemplary gain error is illustrated in FIG. 16. In theexample shown, the gain of the residue amplifier is slightly less than4. As a result, the waveform (“<4×GAIN”) shows a different slope orincline when compared with the ideal waveform (“STAGE 1 RESIDUE Vout”).Furthermore, the transfer function is no longer a straight line, but hasa repeated sawtooth error throughout the transfer function. TheIntergral Non-Linearity (INL) of the ADC is also shown to illustrate thepresence of gain error (note that ideal INL of the ADC is a flat line).Because this residue amplifier is positioned at the boundaries of theplurality of stages of a pipeline ADC, the errors associated with thegain is called the “interstage gain error”. In some embodiments, theideal gain is a gain of 4, but in reality, the gain can end up being,e.g., 3.9, 4.1, etc., and the deviation from the ideal gain can varyover voltage supply and/or temperature. Generally, to calibrate, a known(random) signal can be injected into the stage which passes through thenext stage, and the output signal having the known signal is measured.Determining the error from the measurement enables the gain to becorrected in the digital domain or compensated in the analog domain.

Another source of error in the individual stages is the DAC error, or insome cases, capacitor mismatch errors, and the effect of an exemplaryDAC error is illustrated in FIG. 17. In some cases, the DAC includes anarray of capacitors. Due to many factors, the actual capacitance ofdifferent capacitors do not match precisely as intended. In this case,the DAC includes unit sized capacitors, and a DAC error is present dueto Cdac_(i)≠Cdac_(i-2). As a result, the waveform(“Cdac_(i)≠Cdac_(i-2)”) shows an offset when compared with the idealwaveform (“STAGE 1 RESIDUE Vout”). The INL of the ADC is also shown toillustrate the presence of capacitor (mismatch) errors or DAC errors.Furthermore, the transfer function is no longer a straight line, but hasone or more steps in the transfer function.

The effect of the exemplary gain error and the effect of the exemplaryDAC error are shown in FIG. 18, illustrating a situation where botherrors are present. The waveform (“<4× gain Cdac_(i)≠Cdac_(i-2)”) showsa combination of difference in slope and an offset when compared withthe ideal waveform (“STAGE 1 RESIDUE Vout”). The INL of the ADC is alsoshown to illustrate the presence of both errors.

It is noted that the gain error and/or DAC errors can be measured andcalibrated using the embodiments disclosed herein (e.g., throughdigitally assisted functions implemented by specialized digitalcircuitry and/or on-chip uP).

In some embodiments, the gain error can be measured using a foregroundmethod (e.g., where the converter is not in use, but is either infactory, upon power up, in a test/calibration mode). For example, thegain can be measured using a reference capacitor, at the input of theresidue amplifier, whose energy to be delivered to the output has anexpected value, and the output can be observed or measured with respectto the expected value. The measurements can provide error measurementsfor a given temperature and voltage of the residue amplifier. Theswitching of the reference capacitor and measurements of the output canbe performed by specialized digital circuitry, and the specializeddigital circuitry can store the measurements in a memory that isaccessible by the on-chip uP for calibration. In some cases, the on-chipuP and/or the specialized digital circuitry can perform gain adjustmentin the converter once error coefficients are determined based on themeasurements.

In some embodiments the gain error can be measured using a backgroundmethod (e.g., while the converter is in use). For instance, a random(but known) signal can be added to the input then correlated out in thebackend digital output to accurately measure any change in gain (e.g.,due to any possible source including shifts in DC amplifier gain,amplifier settling, temperature, voltage etc.). The generation of therandom signal and measurements of the output can be performed byspecialized digital circuitry, and the specialized digital circuitry canstore the measurements in a memory that is accessible by the on-chip uPfor calibration. In some cases, the on-chip uP and/or the specializeddigital circuitry can perform gain adjustment in the converter onceerror coefficients are determined based on the measurements.

In some embodiments, the DAC error (e.g., capacitor mismatch error) canbe measured in a foreground calibration method (e.g., where theconverter is not in use, but is either in factory, upon power up, in atest/calibration mode). The input is switched off (e.g., connected toground, or set at 0 volts), the capacitors of the DAC can be switchedindividually up or down, and the output is observed/measured todetermine whether the capacitor is delivering an expected amount ofenergy at the output to assess whether there are any capacitormismatches. The measurements can provide error measurements for a givengain of the residue amplifier. In some cases, the switching of thecapacitors and measurements of the output can be performed byspecialized digital circuitry, and the specialized digital circuitry canstore the measurements in a memory that is accessible by the on-chip uPfor calibration. In some cases, the on-chip uP and/or the specializeddigital circuitry can perform trimming of the capacitors in theconverter once error coefficients are determined based on themeasurements. In some cases, the calibration for DAC error is performedbefore the gain error calibration is performed.

The gain error and the DAC error can be calibrated for any one or morestages of a pipeline ADC. For instance, calibration circuitry can betuned by the on-chip uP to digitally correct the output signal, usingone or more calibration blocks which correct for errors measured foreach stage being calibrated. When many stages are in a pipeline ADC,many individual calibration blocks in the calibration circuitry can bearranged in a reversed order in the signal chain when compared with theorder of the stages in the conversion circuitry. In one embodiment, afirst calibration block can perform correction of errors of one or morelast stages of the pipeline ADC, another block later in the signal chaincan perform correction of errors of a stage of the earlier stages of thepipeline ADC, and yet another block later in the signal chain canperform correction of errors of an even earlier stage of the pipelineADC. Further calibration blocks later in the signal chain can include ablock for correcting kickback error, etc.

Dithering Examples

For a pipeline ADC, a dither can be injected at any one or more of thestages at the summation/difference node of the stage. FIG. 19 shows anexemplary pipeline ADC having 6 stages, equipped with dither injection,according to some embodiments of the disclosure. Dither injection can beperformed using specialized circuitry, i.e., dither generator 1902. Inthis example, dither generator 1902 generates dither signals and injectsthe dither signals in the first three stages. For each stage having adither injected thereto, the dither can have many possible levels. Forinstance, a stage can have 9 dither levels (e.g., the first stage and/orthe second stage can have 9 dither levels). In another instance, a stagecan have 3 dither levels (e.g., the third stage can have 3 ditherlevels). Any number of suitable dither levels can be used. With anon-chip uP 1904, dithering parameters can be controlled by the on-chipuP 1904 coupled to the dither generator 1902. For instance, if the inputfrequency is of a certain range, the number of dithering levels can betuned for the particular input frequency using the on-chip uP 1904.

Generally speaking, the dither help enable the calibration algorithms tobe more independent from the characteristics of the input signal. If theinput signal is very small, the gain can be different when compared witha very large input signal. Dithering can help balance out or average outthe differences that are dependent on the input signal. For instance,the size of the input signal can affect the number of components beingused for a converter, but if a dither signal is injected, the usage ofthe components can be evened out. In some instances, the dithering alsohelps randomize the signal to spread out systematic/periodic errors orspurs in the output spectrum.

In some embodiments, the dither levels for, e.g., a stage 1 of apipeline ADC, can be calibrated for better dithering. The dither signalcan be measured in the foreground or in the background and programmedinto a memory that is accessible by the calibration circuitry to adjustfor or take into account any non-ideal dither signals.

Correlation Based IGE/IME Calibration with Dithering Enabled

For measuring the gain, one exemplary method leverages dithering tomeasure the gain, by computing the ideal dither power (IDP) divided bythe measured dither power (MDP). In some cases, the IDP is measured inthe factory or in the foreground. MDP can change due to changes intemperature or voltage, which suggest there is a gain error in aparticular stage.

A correlation scheme can be used, which is illustrated in FIG. 20. Thebasis of a correlation scheme is that when two signals are uncorrelated,the cross correlation term is zero or substantially zero. The crosscorrelation term “Cross-Corr(x,y)” can equal to sum(x*y). When x=y thenthese are perfectly correlated and is equal to the power. Assuming thedither signal injected into the signal chain is random and uncorrelatedwith the other signals:

-   -   Cross-Corr(Signal*Dither)=Sum(Signal*Dither)^(˜)=0 for a large        number of samples    -   Cross-Corr(Dither*Dither)=Sum(Dither*Dither) is a measure of the        dither power.

Referring back to FIG. 20, the measured input signal “Signal” has thedither signal “Dither” added thereto. A multiply operation is performedusing (known digital version of) “Dither” to obtain“Signal*Dither′+Dither*Dither′”. When “Signal” and “Dither” areuncorrelated, the term “Signal*Dither” should average out to be zeroover time (by means of the low pass filter), and the resulting term“^(˜)Dither*Dither” can be a measure of the dither power. The size of“^(˜)Dither*Dither” (measured dither power or MDP) relative to the(known digital version of) “Dither” squared (ideal dither power (IDP)can indicate a gain error in the stage. The IDP can be measured in thefactory or foreground, in order to take into account any processvariations that can affect the dither power. The MDP can vary from IDPdue to changes in temperature or voltage.

FIG. 21 illustrates a gain error calibration scheme, according to someembodiments of the disclosure. In this example, the signal is denoted as“S”, the dither signal is denoted as “d”, and the DC offset is denotedas “dc”. The example shows S+d+dc is multiplied with the dither signal.The result of averaging S+dc*d+d^2 should result in the MDP. TakingIDP/MDP results in the gain error (“Gain_Error”). The gain errormultiplied by the dither signal (Gain_Error*d) can be used to correctthe signal “S+d+dc” (by subtraction, i.e., “S+d+dc−Gain_Error*d”). It isnoted that the gain error calibration scheme using correlation andaveraging over a long period of time means gain error coefficients areupdated rarely since long averages are needed (e.g., millions ofsamples). This means the gain error calibration scheme (at least inpart) is particularly suitable for being carried out by the on-chip uP.Furthermore, the scheme can be performed for the whole pipelineconverter, or for one or more selected stages of the pipeline converter.The illustrated scheme is considered to have a feed forwardconfiguration.

FIG. 21 illustrates another gain error calibration scheme, according tosome embodiments of the disclosure. This scheme is a least mean squared(LMS) process in a feedback configuration. The gain error,“Dither_Gain_Error” is determined and multiplied with the dither signal“I_Dither” to obtain “Dither_Gain_Error*I_Dither”. The“Dither_Gain_Error*I_Dither” is added to “I_Dither” to obtain“Dither_sub”. “I_input” is then subtracted by “Dither_sub” to obtain“O_Output”. During the calibration process, the input“I_input-Dither_sub” (“FB_Input”) is multiplied with “I_Dither”. Theresulting value “mix” is accumulated for a long period of time and isdecimated to slow down the clock rate (e.g., by 1024 times). In someembodiments, the accumulation can be implemented using a cascadedintegrator comb structure. Furthermore, the accumulated value“Dec_accum_out” is multiplied by a small number to obtain the average,and the average is used for obtaining the gain error (e.g., representedby “Dither_Gain_Error” and “O_Gain_error”). Also for this scheme, theupdating of the measured gain error changes very slowly. This means thegain error calibration scheme (at least in part) is particularlysuitable for being carried out by the on-chip uP. The decimatingaccumulator 2202 can be implemented using specialized circuitry (digitaland/or analog). The part 2206 which relates to adaptation and slowlydetermining the gain error and computing of corresponding gain errorcoefficients can be implemented using the on-chip uP (at a rate that isfar slower than the converter system). Furthermore, the scheme can beperformed for the whole pipeline converter, or for one or more selectedstages of the pipeline converter. The illustrated scheme is consideredto have a feed forward configuration.

Another scheme can involve driving the dither signal in the residue tozero using the correct gain (by multiplying the digital representationof the dither signal with an error coefficient, and subtracting theresidue signal with the digital representation of the dither signal*anerror coefficient). One example includes using 2-tap finite impulseresponse filter (FIR) and LMS to background calibrate the gain/memoryerror. The scheme can compute error coefficients for the (flash) ADCfrom adapted/learned calibration and gain error. The gain from earlierstages can be applied and passed onto the later stages in from earlierstages. The scheme may include circuitry for measuring the gain error,as well as computation blocks for computing error coefficients foradjusting the (flash) ADC of the stage and/or the dither signal. Theon-chip uP can be used for implementing the functions of at least someof the (algebraic/arithmetic) computation blocks for computing errorcoefficients for adjusting the (flash) ADC of the stage and/or thedither signal. The on-chip uP can also provide checks on the errorcoefficients to ensure that the error coefficient does not go beyond asuitable range, because an inappropriate error coefficient candrastically affect the gain of the system and cause catastrophic errors.

On-chip uP can Combine Capacitor Trimming and IGE Calibration

FIG. 23A-B show an exemplary calibration functions suited for beingcarried out by the on-chip uP, according to some embodiments of thedisclosure. In some cases, the calibration involve computing acorrection term, e.g., an additive correction term, for the signal path.A look up table can be used for each sub-range to look up the correctionterm, and the on-chip uP 2302 can advantageously perform thecomputations for generating the correction terms. In FIG. 23A, the lookup table has the nominal bit weight of the stages built-in, e.g., for a3-bit flash ADC. For the 3-bit flash ADC example, the captrim_corr_coefcan replace the flash output data. In FIG. 23B, this lookup tableassumes that the nominal weight of the flash stage is handled using anaddition in the high speed path. The nominal weight W is typicallyapplied with a bit-shift and add. This can reduce the size of the lookuptable at the expense of another adder. For this example,captrim_corr_coef can be added to the residue. This example shown inFIG. 23B could require less hardware (e.g., muxes) since the correctionterms are smaller than the example shown in FIG. 23A.

In the example shown, the correction for IGE and for the capacitor error(DAC INL, or capacitor trimming, or any suitable non-linearity error)can be performed together using the resulting correction term“captrim_corr_coef” (used as a correction term, or an additivecorrection term, e.g., a term to be added to the residue output signalof a particular stage). To generate the correction terms (that areeasily selectable by the flash ADC output data “flash data” using themux), each capacitor error coefficient per code (in this case there are3 bits, thus 9 codes) are individually added by a gain correction termhaving each code multiplied by the gain error (“Gain_Error placed instage”, e.g., −4*ge, −3*ge, −2*ge, . . . , +3*ge, +4*ge). The updatingor computation of correction terms coef_sub[x] (in this example, 9coefficients) can be computed easily using the on-chip uP 2302.Performing such calculation to generate all coefficients (easilyselected by the flash ADC output data via the mux) during the updateusing the on-chip uP 2302 instead of having to perform multiply usingdedicated hardware each time the coefficient is needed by the signalchain can greatly improve the efficiency of the system. Also, when thereare many stages and many channels (e.g., in an interleaved ADC), theon-chip uP can reduce the need to provide specialized multiplicationcircuitry for each of the stages and each of the channels.

The gain error can be combined with capacitor errors or other additiveterms into a small lookup-table for each stage. This is applied bymultiplying the signed integer representation of the stage's digitaloutput data (e.g., −4, −3, −2, −1, 0, 1, 2, 3, 4,) by the gain to beapplied and then adding one term per subrange, as illustrated by FIGS.23A-B.

The following code illustrates the lookup table where the gain error(GE) is in the lookup table. For subrange_index = 0 to 8  flash_code =subrange_index − 4  DAC_LUT[subrange_index]=(flash_code + subrange_err[flash_code])*GE End For

On-chip uP can Change the Speed of Adaptation

Generally speaking, calibration algorithms (or training/adaptationalgorithms) are implemented to adjust error coefficients (sometimesreferred herein as correction terms). The adjustment of errorcoefficients is preferably performed at a slow rate so as to not causeabrupt changes in the system. With an on-chip uP, a program can beexecuted by the on-chip uP to adjust the rate of training/adaptation.For implementations where averaging is used, the rate oftraining/adaptation is associated with the number of samples being usedfor the averaging in an accumulator, or a term used for dividing theaccumulated value when computing the average. The adjustment can be madebased on temperature, measurements of the input signal, or othersuitable measurements which may indicate whether the state of the chipis likely to be changing quickly or slowly. For instance, if thetemperature (e.g., measured by a temperature sensor on the chip)indicates fast/large changes in temperature, the training/adaptationrate can be increased to more quickly. In another instance, if the inputis relatively large, the rate can also be adjusted accordingly. In manycases, one or more coefficient in the training/adaptation algorithm canbe adjusted by the on-chip uP to change the convergence time of thealgorithm. Stability of the system can be improved.

On-chip uP can Implement Trimming or Calibration Sequence

One advantage of the on-chip uP is the ability to allow for changes orprogramming of the calibration sequence without having to change theunderlying converter or calibration circuitry. Calibration sequencerefers to the order in which parts of circuitry of the converter arecalibrated, e.g., what is to be calibrated, which stage is calibratedfirst, which part of the stage is calibrated first, etc. During thedesign phase, designers have a particular calibration sequence. Duringthe validation phase, engineers may have a different calibrationsequence, or a different calibration scheme. The differences incalibration sequences can be attributed to different environments fortesting the circuitry. For this reason, having an on-chip uP being ableto execute any selected or desirable calibration sequence or calibrationschemes can significantly reduce the need to re-design or re-implementcircuitry to accommodate the new calibration sequence. The calibrationsequence can be even selected at factory or at the user to improvecalibration via an interface to the on-chip uP, if desired.

On-chip uP can Assist Comparator Trimming/calibration

Generally speaking, the comparators are switched in and out to measureany comparator offsets that may be present. The following outlines anexemplary method:

-   -   Step 1—Short all the comparators to the common mode (ground).        Set all the offsets to all comparators to the low side. All of        the comparators would have zero outputs so the −8 code would        come out of the backend flash.    -   Step 2—Start increasing the offset control to one comparator        until its output flips from 0 to 1. When this happens the output        code will change from −8 to another code. As soon as it toggles        then one of the trims on either side should be taken.    -   Step 3—Repeat Step 2 for each of the comparators individually.        The output of the backend flash, indicative of the comparator        offset, can be mapped to a register for this mode.

The on-chip uP can serve as a controller for switching the comparatorsto the proper state according to the above mentioned series of steps tomeasure offsets for one or more of the comparators. Furthermore, theon-chip uP can determine one or more error coefficients for compensatingor correcting the error based on the measured offset.

On-chip uP can be Suitable for Performing Algebra to Compute Errorsand/or Error Coefficients

Determining the error from measured signals is not always trivial.Usually, a mathematical model is provided for describing therelationship of the error with respect to one or more measured signals.To determine the error, one or more algebraic computations may beexecuted to derive or solve for the error. For instance, the algebraiccomputations can involve computing correlations, and/or determiningdifferences between the measured signals (or an average thereof) withrespect to reference signal(s). These algebratic/arithmetic computationscan, in some cases, be implemented and executed easily by the on-chip uP(or a combination of dedicated digital circuitry and an on-chip uP).

Furthermore, determining the error coefficients from measured ordetermined error is not always trivial. For example, in a pipelined ADC,the gain error coefficients can depend on the gain of the previous orlater stage(s). Usually, the exactness for the gain error coefficientsis important for interleaved converters where the gain for eachinterleaved channel is to be matched against other interleaved channels.For this reason, the gain error coefficients are computed using complexalgebra to properly correct the gain error(s) in the signal chain. Thesealgebratic computations can, in some cases, be implemented and executedeasily by the on-chip uP (as opposed to dedicated hardware computationblocks). Gain error or other slow changing error is assumed to notchange very often, thus, the updating of such errors can be performed bythe on-chip uP (or in some cases, slow speed dedicated hardware).

Having the on-chip uP to execute at least one or more ofalgebraic/arithmetic operations can alleviate the need to providespecialized digital circuitry or hardware for implementing thesefunctions. This advantage is particularly significant in interleavedpipeline ADCs where the on-chip uP can replace (at least in part)specialized digital circuitry which may have to be provided for eachstage of the pipeline ADC for each the interleaved channels.Furthermore, the advantage is significant in interleaved pipeline ADCswhere the inter-related stages and interleaved channels may prompt morecomplex algebraic computations (that the on-chip uP can easily compute).

In some embodiments, dedicated digital circuitry can be used to performthese operations (without requiring an on-chip uP).

On-chip uP can Program Analog Circuitry

With the measurements taken specialized digital circuitry, and theon-chip uP can determine error coefficients usable for programming theanalog circuitry. The analog circuitry often includes many digitallycontrols, bias current, bias voltages, trimmable capacitors. Normallythe configuration of the digital controls are determined based onreviewing many units from a number of processing lots during productcharacterization time to determine the best coefficients. With theflexibility of the on-chip uP, the digital controls can be configured orreconfigured after the converter is shipped to the user.

In one example, the on-chip uP can use a capture memory (e.g., captureRAM) to perform an on-chip Error Waveform (EWF) to determine transitionpoints of the comparators in any one stage of a pipeline ADC (e.g.,stage 1) or a reference ADC. Coefficients can be computed by the on-chipuP and be used to set one or more fuses to trim the capacitors.Accordingly, the on-chip uP provides the ability to digitally trim thecomparators to improve the flash ADC comparators.

Exemplary Digitally-assisted Interleaved ADC

FIG. 24 shows an exemplary system diagram of an exemplary interleavedADC having an on-chip uP, according to some embodiments of thedisclosure. The architecture of an interleaved ADC is described inrelation to FIGS. 7A and 7B. FIG. 24 is similar to FIGS. 10-11, butshows illustrates some additional system components. The system 2400includes a plurality of sub-ADCs 2402. Optionally, the system 2400 caninclude a reference ADC which can sample the input signal at a lowerrate than overall interleaved ADC, but when the reference ADC issampling, it generally samples at the same time when any one of thesub-ADCs is sampling the input signal. The reference ADC be used as areference or provide a reference measurement signal for calibrationalgorithms. One or more ones of the sub-ADCs can have a respectivedither generator 2406 and/or registers 2408. The registers 2408 can beaccessible by the respective one or more ones of the sub-ADCs, e.g., toretrieve error coefficients to adjust the signal chain. An on-chip uP2410 can access (read and/or write) to the registers 2408, e.g., witherror coefficients usable for calibration. The output signals of thesub-ADCs 2402 and reference ADC 2404 are provided to respectiveinterfaces 2410 and 2412, which can prepare the output signals (e.g.,digital data) for the calibration logic 2414. The calibration logic 2414can digitally correct the output signal from the sub-ADCs 2402 beforethe digital data is exported for output via a suitable interface, e.g.,JESD interface 2416 or preferably a fast or high bandwidth datainterface. The calibration logic 2414 can, in some cases, be integratedwith the sub-ADCs 2402 for correcting errors in the analog domain. Aclock divider 2418 and sampling sequencing 2420 can be provided togenerate suitable clock signals for the sub-ADCs 2402, the reference ADC2404, the calibration logic 2414, and the on-chip uP 2410. Samplesequencing 2420 can implement sequential sampling of thetime-interleaved sub-ADCs 2402 or a randomized (or pseudo-randomized)sampling of the time-interleaved sub-ADCs 2402. Clock divider 2418and/or sample sequencing 2420 can implement spread spectrum clocking forany one or more of the clock signals.

Advantageously, the calibration logic 2414 can implement accumulationand/or decimation to gather measurements of the outputs of the sub-ADCs2402 and/or the reference ADC 2404 that the on-chip uP can process at aslower rate than the sampling rate of the sub-ADCs 2402 and/or thereference ADC 2404. The calibration logic 2414 and the on-chip uP 2410can communicate over the bus logic 2422. The on-chip uP 2410 can includeinternal memory or closely coupled memory, e.g., on-chip uP randomaccess memories (RAM(s)) 2424. The memory for the on-chip uP 2410 canstore a variety of data used by the training/adaptation algorithm(s)implemented on the on-chip uP 2410, including one or more of thefollowing: inputs to the algorithm(s), intermediate values of thealgorithm(s), measured error(s), and error coefficient(s). The memoryfor the on-chip uP 2410 can store instructions executable by the on-chipuP 2410 to carry out the training/adaptation algorithm(s).

To provide a debug feature, the system 2400 can include a debug memory,e.g., debug RAM 2426, for storing or logging data measured by thecalibration logic 2414, data values computed by the on-chip uP 2410,etc. The data can enable a user to gather data during a debug mode ofthe system 2400. To allow a user to access the system 2400, a suitableserial interface (e.g., Serial Peripheral Interface (SPI) slave) can beprovided to allow a user to read and/or write to memory elements of thesystem 2400, including one or more of the registers 2408, debug RAM2426, and uP RAM(s) 2424, etc. This allows a user to write and configurethe system 2400, read from debug RAM to obtain data for analysis, and/orwrite to uP RAM(s) 2424 to configure the functions of on-chip uP 2410.These exemplary functions are for illustration and are not intended tobe limiting.

In one example, system 2400 can be implemented using 28 nm technologynode, with 12-bit resolution at 10 giga samples per second (GSPS),having eight interleaved sub-ADCs with random and sequential samplingmodes.

An on-chip dither generator (e.g., dither generator 2406) can beprovided for each sub-ADC, and the overall system 2400 can be calibratedfor interstage gain, interleaving errors including, e.g., offset, gain,and timing, sample order dependent interleaving errors including, e.g.,offset, gain, and timing. The on-chip uP 2410 can be used to executeslower speed processing (slower with respect to ADCs, or even thecalibration logic 2414).

In some embodiments, each sub-ADC is a pipeline ADC, and the calibrationlogic 2414 can have a respective calibration block for one or morestages of pipeline ADC. For example, a pipeline ADC having five stagesmay have five calibration blocks, or less, if some stages are not to becalibrated. The calibration block can compensate for capacitor mismatcherror and interstage gain error. Correlation can be run with measuredsignals or data from the stages of the pipeline ADC and provide data ata lower clock rate. The on-chip uP 2410 can perform adaptive coefficientupdates and computes correction coefficients to be used by calibrationlogic 2414, and stored in registers 2408 of the sub-ADCs. The on-chip uP2410 can write error coefficients to registers in calibration logic 2414or registers 2408 of the sub-ADCs. Furthermore, the on-chip uP 2410 canimplement control functions for system 2400. In some cases, the on-chipuP 2410 can provide supporting functions for testing, debugging, etc.

Exemplary Error Coefficients and Data Used for Calibrating a PipelineADC

FIG. 25 shows an exemplary hardware flow for flash ADC calibration andpipeline stage calibration, according to some embodiments of thedisclosure. This example is applicable for multi-stage ADCs (includingpipeline ADCs) in general, and for pipeline ADCs used as sub-ADCs intime interleaved ADCs. The FIGURE shows a flash ADC calibration block,e.g., flash_cal 2502 (for compensating errors of the back end flashADC), a pipeline stage calibration block, e.g., stg_cal 2504 (forcompensating errors in a particular stage of a pipeline ADC). Multipleones of the pipeline stage calibration block can be provided formultiple stages of the ADC (e.g., one per stage). The calibration blockscan be implemented digitally, where coefficients can be selected using amux, and applied to an output signal to digitally compensate for one ormore errors. For some calibration blocks, the following list provides anexemplary description for the signals, which can be provided to theon-chip uP for calibration or can be written in registers by the on-chipuP for calibration:

2506 Can be 2506 can be implemented as a look-up table using a mux; 2506can generated by be used to calibrate the back end flash ADC of apipeline ADC. The on-chip uP mux can select the appropriate errorcoefficient based on the digital data such that the appropriate errorcoefficient can be added or applied to the signal to digitally correctfor comparator mismatches (effectively trim the comparators) in the backend flash ADC. 2508 Can be 2508 can correct for gain change and/orprovide capacitor trimming; generated by This represents a look up tablefor storing coefficients or correction on-chip uP terms that can adjustthe transfer function of a stage for correcting errors in a stage. Thetransfer function can take into account gain, capacitor errors, etc.Rather than a single look up table (as shown in this FIGURE), delayblock(s) and multiple look up tables can be used to implement a finiteimpulse response filter to adjust the transfer function of the stage orcorrect an error of a particular stage. 2510a, Can be 2510a and 2510bare programmed by the on-chip uP to be two 2510b, generated by different(expected) levels to be used as the random or dither signal on-chip uPfor the correlation (the random or dither signal referred herein asRCAL, in some cases correct for offset trim), and the two differentlevels are selected by RCAL 2512. 2512 Generated 2512 can be provided tothe correlator for error measurement, by RCAL cap which can be used tomeasure capacitor transitions and/or drive the (or dither RCAL signallevel present at node (node with the expected level of DAC for RCAL2510a/b has been subtracted from the calibrated residue) to generatingzero. RCAL) 2514 Provided to 2514 comprises data of a lower rate (e.g.,generated by on-chip uP accumulation and decimation) usable by theon-chip uP to compute error(s) and/or error coefficients for correctingerrors of the stage (e.g., to update 2508).

Example:Calibrating Capacitors (“Caps”) of a Stage of a Pipeline ADC(“Cap-Cal”)

One task is to remove step errors in the transfer function so that a bittoggle in a particular stage matches the change in the backend residue.For example, in stage two, each bit is weighted by 64, when toggled theresidue should nominally toggle +Vref/4 to −Vref/4 which shouldnominally resolve to +32/−32, offsetting the step. If cap is too small,it may only jump from +32 to −29. DAC capacitor calibration (“DACcap-cal”) can compute this difference and subtract 3 from the outputwhen in this subrange.

In some embodiments, calibration can start at stage 4 and calibratebackwards ending at stage 1. Such a scheme can allow a corrected backendto be used for measurements.

In some embodiments, calibration involves biasing the stage to +/−Vref/4using the stage 1 dither-DAC. Toggling the cap of interest from +/−Vrefcan toggle the residue to −/+Vref/4. The change in the backend can bemeasured and averaged over N samples. Deviation from expected value canbe calculated and saved as cap-error values. Dedicated hardwarecorrelator used in interstage gain error calibration can be reused orused for this measurement. Subrange correction values are computed ascumulative sums of cap-error values. The cumulative sums of cap-errorvalues can be applied for calibration the capacitors.

In some embodiments, a dither search algorithm is used to bias eachstage to +/−Vref/4. Caps 1-8 can be nominally tied to +Vref; these needstage to be biased to +Vref/4 so that when they toggle we jump to−Vref/4. Caps 9-16 can be nominally tied to −Vref; need bias to −Vref/4.Dither search algorithm can be performed in each stage immediatelybefore DAC capacitor calibration (“DAC cap-cal”). The algorithm isuseful because due to non-idealities it is not known exactly how muchdither is required to bias a later stage to +/−Vref/4. Expected backendoutput for +/−Vref/4 bias is:

-   -   expected_output[stg]=+/−stage_weight[stg]/2.

Dither search algorithm can involve a series of steps:

-   -   Unlock all flash stages    -   Start with dither at full scale negative    -   For i=1:7 loop        -   Average output for N cycles        -   If difference between average and expected greater than            nominal dither[i], toggle dither[i] for next round    -   Repeat twice, once for +/−Vref/4, and save dither values for        each to use in biasing during DAC cap-cal    -   During DAC cap-cal, LOCK the front-end flash stages so that        biasing point is maintained

Measuring DAC-caps involves computing size of each DAC step:

${{cap}_{{size}{\lbrack n\rbrack}} = {\frac{1}{N}*{\overset{N - 1}{\sum\limits_{i = 0}}{{{{cap}\_{sign}}\lbrack i\rbrack}*{{residue}\lbrack i\rbrack}}}}},{n = 0},1,{\ldots\mspace{14mu} 15}$

Compute cap error can involve computing the following:expected_cap_size[stg]=stage_weight[stg]/2cap_error[n]=expected_cap_size[stg]−cap_size[n]

Sum to form final adjustment for subrange:subrange_err[k]=Σ _(i=0) ^(k-1)cap_error[i]−Σ _(i=k) ¹⁵cap_error[i],k=0,1,2 . . . 16

Example: Forming Baseline for Random or Dither Signal (“RCAL”) DAC orRCAL Capacitor Calibration (“Cap-Cal”)

The task is to measure the RCAL cap in each stage (used in a DAC togenerate the random/dither signal being used for the correlation) usingthe corrected backend to form the baseline for the interstage gain errorcalibration. The task involves calculating rcal_weight variable for IGE,which is used as the baseline for interstage gain error backgroundcalibration. This task, “RCAL cap-cal”, can be performed after the DACcap-cal for that stage.

In some embodiments, RCAL cap is nominally ⅛th size of DAC-cap; togglingit swings the output by Vref/16 magnitude (Vref/2 for DAC-caps). Due toamplifier nonlinearity, gain is larger near 0 than Vref/4. Where weoffset the amp before toggling RCAL can affect how large it appears inbackend. To get a “best fit”, dither can be used during RCAL capmeasurement. Let dither-DAC in stage 1 run freely at half-speed. Toggleeach RCAL cap at full speed, and use existing correlators to measureRCAL size. By running at half-speed, dither can cancel for each RCAL captoggle, so it doesn't need to be averaged out as noise. Measuring RCALcaps can involve computing the following:

${{{rcal}\_{weight}}\hat{}\lbrack n\rbrack} = {{\frac{1}{N}*{\sum\limits_{i = 0}^{N - 1}\;{{{rcal}\lbrack i\rbrack}*{{residue}\lbrack i\rbrack}}}}❘_{{{dith} = {{rand}{({{div}\; 2{clk}})}}}{{rcal}\mspace{14mu}{toggle}\mspace{14mu}{every}{\mspace{11mu}\;}{clk}}}}$

Example: Dither Capacitor Calibration

The task is to measure each binary-weighted dither cap in the S1dither-DAC using the corrected backend so that the dither can beaccurately subtracted out digitally (to avoid a hit to thesignal-to-noise ratio). This task can be performed after DAC cap-caland/or RCAL cap-cal. Similar to RCAL cap-cal, the task tries to get a“best fit” of the nonlinearity.

In some embodiments, cap-cal is performed one capacitor at a time (e.g.,there are 7 dither caps). The cap-cal lets the 6 other dither capsrandomly toggle on a div2 clk, and toggles the other cap (the cap undercalibration) every clk cycle, similar to RCAL cap-cal. The 6 otherdither bits cancel out, so averaging them out as noise is not necessary.Measuring dither caps can involve computing:

${{{dith}\_{weight}}\hat{}\lbrack n\rbrack} = {{\frac{1}{N}*{\sum\limits_{i = 0}^{N - 1}{{{{dith}\_ n}\lbrack i\rbrack}*{{residue}\lbrack i\rbrack}}}}❘_{{{{dith}{\lbrack{j \neq n}\rbrack}} = {{rand}{({{div}\; 2{clk}})}}}{{{dith}{\lbrack n\rbrack}}\;{t{oggle}}\mspace{14mu}{every}{\;\;\;}{clk}}}}$

Example: Interstage Gain Error (IGE) Correction

Interstage gain error (IGE) correction or calibration involvescalibrating the Inter-stage Gain Error of stages 1-4 in all 8 subADCs. Aknown signal, e.g., a random signal, is injected onto the summing nodeof each stage. Injecting the random signal to each stage allows theinterstage gain of each stage to be separately and independentlydetermined. Calibration signal can be a 2 level pseudo-random RCALsignal, which can be run at Fs/2, Fs/4, Fs/8, Fs/16 for FG/debug. It canbe forced to +/−1. RCAL progresses through the same amplifier and ADCbackend (BE) stages as the desired signal. A Foreground or FactoryMeasurement of the baseline power out of the backend stages sets abaseline operating point. At the baseline, IGE^(˜)=0 (foreground cap-calcan make this zero). Any changes in the power of the RCAL duringoperation is considered to be because of a change in the gain of theamplifier and BE Stages. These changes are usually presumed to bechanges in the Voltage/Temperature (VT) operating point. This gainchange is assumed to be correct and applied to the main path. Acorrelation based LMS algorithm can be used to minimize the RCAL out ofthe backend (BE). This removes RCAL and senses the gain at the sametime. The analog sub-ADC pipeline can be modeled by the followingequation:R=[(S−DAC[flash_code])*Gnom+rcal*rcal_weight]*(1+IGE)

The RCAL signal is the 1-bit random signal injected into each stage.rcal_weight represents the size of the RCAL (analog) injection for theforeground process-voltage-temperature (PVT) operating condition. Thisreflects the cap size and the baseline amplifier gain.

For IGE the digital tries to minimize the following error signal (e.g.,signal which is left behind when the random signal is removed):error=(R*(1+IGE_corr))−rcal*rcal_weight^

This only happens when the:rcal_weight^=rcal_weight*(1+IGE)*(1+IGE_corr)

IGE is variation from the baseline PVT. Assuming rcal_weight rcal_weight(Assuming cap-cal was accurate), then:

${{IGE}{\_ corr}} = {\left( \frac{1}{1 + {IGE}} \right) - 1}$

The “error” signal to be driven to zero is used in the correlationprocess:error=(R*(1+IGE_corr))−rcal*rcal_weight^

A hardware correlator can be used to average N samples of theerror*rcal.

${rcal}_{c\; o\; r\; r} = {\sum\limits_{{sn} = 0}^{{sn} = {N - 1}}\;{{error}*{rcal}}}$

This is a 1-bit rcal*error so it is just a mux and an accumulator. TheCorrelator outputs are read directly by the on-chip uP and furtheraveraging can be applied:IGE_corr+=μ*rcal_(corr)

μ Can be controlled by the on-chip uP to control how quickly the errorcoefficient is to be updated.

The IGE_corr from this stage is then applied to the Residue to form afeedback loop. IGE_corr is combined with the cap information and mappedto the correction hardware (as illustrated by FIGS. 23A-B). Note thatthe gain correction IGE_corr is being applied to the residue signal Rerror=(R*(1+IGE_corr))−rcal*rcal_weight^

In order to avoid a high resolution multiplier for this multiplication,the multiplication is distributed through the back-end gain stages. Forexample for Stage 1, the correction is the following:R1_corr=(1+IGE_corr_stg1)*[F2<<6+F3<<4+F4<<2+F5]

Since the equation is linear the multiply can be distributed to all theflash stages. For stages 2-5 the flash is multiplied by a term thatincludes the stage 1 gain. For stages 3-5 we have a term that includesthe Stage 1 and Stage 2 gain, etc. For instance, the stage 3 IGEcorrection term can include the stage 1 and stage 2 gain:IGE_corr_stg3=(1+IGE_corr_stg1)*(1+IGE_corr_stg2)−1

−1 in the above equation is due to the additive error model being used.A new variable applied_gain_corr can be introduced to reflect that thegain accumulates as the process goes from Stage 1 to Stage 5. Also, a“Stage 0” gain can be used to change the overall gain of a subADC. Thevariable(s) are useful for Interleaving Cal or for general gainadjustment (interleaving gain calibration). The computation ofapplied_gain_corr can be performed by the on-chip uP. Pseudo code forcomputing applied_gain_corr is as follows:

//Compact C description for computing cumulative gain gain_cum[0] = 1 +Gain_Error; // Channel Gain of subADC for other purposes for(stg_index=1;stg_index<5;++stg_index)  {   applied_gain_corr[stg_index] =gain_cum[tg_index − 1] − 1.0;   gain_cum[stg_index] =applied_gain_corr[stg_index] *   (1 + ige_corr[stg_index]) ;  rcal_level[stg_index] = rcal_weight{circumflex over ( )} *  applied_gain_corr[stg_index] ; }

In some embodiments, capacitor trim and IGE correction as mentionedabove can be combined into one look up table, using the followingequation, whose computation can be performed by the on-chip uP:DAC_LUT[flash_code]=(flash_code+subrange_err[flash_code])*applied_gain_corr

The procedure for computing the values of the lookup table using a muxwas previously illustrated in FIG. 23A-B, where both IGE and capacitorerrors (or other additive errors) are both taken into account by thevalues in the look up table selectable by the flash output code.Generally, the uP can compute values for the DAC_LUT[*] and writes thevalues to hardware. Advantageously, the uP alleviates the need toimplement dedicated hardware multipliers, since the computationinvolving multiplications are performed by the uP. A further advantageinvolves combining the IGE and capacitor trip values together in onelook-up table where the values from the look up tables can be added tothe residue (as an additive correction term).

The following outlines, as another example, how the gain can be appliedto later stages of the ADC.

-   R*: Digital residue of a particular stage-   S*: Flash data of a particular stage-   W*: Weight of a particular stage-   GE*: Gain Error of that stage.-   Gain*: Gain for that stage, expressed as (1+GE)-   W_Gain*: The actual gain applied for a particular stage. This is a    function of the gain error measured for that stage and gain error    from earlier stages.    R4=S5*W5 (residue of stage 4 is the flash data of stage 5*the weight    of stage 5)    R3=R4+S4*W4    R2=R3+S3*W3    R1=R2+S2*W2    R0=R1+S1*W1 (ADC Output)    R0=ADC=(S1*W1+S2*W2+S3*W3+S4*W4+S5*W5)*IL_GAIN*CH_GAIN-   IL_GAIN: Interleaving gain (optional), a possible coefficient for    changing the gain of the entire subADC channel for interleaving    calibration-   CH_GAIN: Channel gain (optional), a gain setting for the ADC channel    for use by the customer or for Quadrature Error Correction (QEC).    CH_GAIN would be applied to all subADCs.    W1=256*(1+GE1) - - - Represents only the gain of that stage.    W2=64*(1+GE2)    W3=16*(1+GE3)    W4=4*(1+GE4)    W5=1-   Math passing the gains down the pipe to change the gain of each    stage, using recursion, so that gain of a stage takes into account    for gain of the previous stage(s)-   W_GE*: accumulated weight or gain to be applied, or “cumulative gain    term”    W_GE1=(1+IL_GAIN)*(CH_GAIN)    W_GE2=W_GE1*(1+GE2)    W_GE3=W_GE2*(1+GE3)    W_GE4=W_GE3*(1+GE4)    W_GE5=W_GE4-   Note: The accumulated weight (or “cumulative gain term”) replaces    the weight of the particular stage to correct for IGE. The    accumulated weight (or “cumulative gain term”) is a function of    everything that came before (as outlined above).    ADC=(S1*W_GE1+S2*W_GE2+S3*W_GE3+S4*W_GE4+S5*W_GE5)*IL_GAIN*CH_GAIN-   This equation is linear, thus the gain term for each stage can be    distributed to individual stages, and the multiplication for    computing the additive correction terms taking the cumulative gain    term into account can be calculated by the on-chip uP.

Using the above calculations for IGE, a dedicated memory element can beprovided for each residue to be corrected. The dedicated memory elementcan serve as a look up table to store additive correction terms beingused for each possible digital output code of the particular stage (oreach subrange of the residue). Typically, a small look up table is beingprovided to correct capacitor errors already, thus, correcting the gainusing the same small look up table (e.g., as illustrated in FIG. 23A-B)means it would not incur additional circuitry. The result is a veryefficient architecture for correcting IGE. In some conventionalapproaches, a single large look up table having thousands ofcoefficients are used to store calibration coefficients, or a dedicatedhigh speed multiplier is provided to correct each stage. Large look uptables (storing thousands of coefficients) not only take up area, thelook up operation is considerably slower than smaller look up tables(storing tens of coefficients). In the other conventional approach,using a dedicated high speed multiplier is problematic because it islarger and more power hungry then using a small look up table and anadder for correcting IGE.

Generally speaking, the correction term (or error coefficients) storedin these look up tables can be additive, or it could replace data in thesignal path with a corrected value. The choice of either option candepend on the application and implementation.

Applying Linear Filters as Additive Correction Terms to the Residue

Applying a multiplicative gain term can be considered as applying aone-tap linear filter to the residue of a stage. Leveraging the sameconcepts as above, it is possible to apply a linear filter, e.g.,implemented with multiple taps, and to apply the linear filter tocorrect a particular stage using multiple look up tables (one look uptable for the residue, one or more look up tables for delayed version(s)of the residue). Linear filters implemented with multi-tap filters canbe useful for addressing memory effects when correcting the particularstage (e.g., the residue output signal). The current output code canselect one (additive) correction term from one look up table; a delayedversion of the output code can select a further (additive) correctionterm from a further look up table. The final (additive) correction termto be applied to correct the stage (e.g., the residue output signal) canbe a sum of the selected (additive) correction term and the further(additive) correction term. For more taps, additional delay can beapplied and further look up tables can be used. Outputs from the look uptables are summed together to generate the final correction term

When dealing with linear filters being applied to cascaded stages,calculating (additive) correction terms for a given stages (i.e., valuesin the look up tables) can take linear filter(s) of previous stage(s)into account. Phrased differently, a cumulative linear filter can beindividually applied for each stage, where the cumulative linear filterwould take into account the linear filter of a given stage with thelinear filter(s) of previous stage(s). To compute taps of the cumulativelinear filter, the filter taps of the linear filter of the given stageand filter taps of the linear filter(s) of the previous stage(s) can beconvolved with each other to generate the cumulative linear filter forthe given stage.

A linear filter for each stage can be determined using a multi-tap formof the least means squared algorithm (similar to ones described herein).Frequency dependent errors of the stage can then be corrected, e.g., inaddition to the gain term. Errors corrected this way are often referredto as memory errors where the current sample of the residue dependspartially on a weighted sum of correction terms for the present sampleand one or more previous samples. Separate look up tables can beprovided for the current output code and delayed version(s) of theoutput code. Phrased differently, the filter (if implemented as a finiteimpulse response filter) can have multiple taps taking the output codeas input, and each tap of the filter can have a respective look uptable. Since the look up tables are small, implementing and using suchlook up tables can be done very efficiently (especially when the on-chipuP can be used to compute updated coefficients).

Note that the mathematical formulation for applying the linear filtersto the stages of the converter is similar to the mathematicalformulation outlined above for gain error. The weights for the gainerror can be modeled in the frequency domain as a function of z, andmultiplication is replaced with convolution. This allows a single highspeed digital filter to be replaced with smaller digital filters wherethe word widths are in the flash data (output code). In a similarfashion as correcting gain, the (additive) correction terms can correcteach stage in a very efficient manner, even when the linear filters havemultiple taps. Small look up tables replace any multipliers which wouldhave been otherwise needed to provide the linear filters. If capacitorerrors are to be included in the look up tables, the first tap caninclude such additive capacitor error term.

-   Suppose the linear filter for each stage is modeled as a 2-tap    filter, the mathematical formulation can be as follows:-   The first stage can be modeled using the following, where C* refers    to the coefficients of the filter taps of the linear filter    corresponding to a particular stage    C1₀ +C1₁ ·z ⁻¹-   If stage 2 and stage 3 have similar 2-tap filter forms as above,    then the cumulative linear filter to be applied into stage 2 would    be given by the product of the polynomials or by a convolution of    the coefficients:

(C 1₀ + C 1₁ ⋅ z⁻¹) ⋅ (C 2₀ + C 2₁ ⋅ z⁻¹)${C\;{1_{1} \cdot C}\;{2_{1} \cdot \left( \frac{1}{z} \right)^{2}}} + \frac{{C\;{1_{0} \cdot C}\; 2_{1}} + {C\;{1_{1} \cdot C}\; 2_{0}}}{z} + {C\;{1_{0} \cdot C}\; 2_{0}}$The cumulative linear filter to be applied into stage 3 would be:

${{{\left( {{C\; 1_{0}} + {C\;{1_{1} \cdot z^{- 1}}}} \right) \cdot \left( {{C\; 2_{0}} + {C\;{2_{1} \cdot z^{- 1}}}} \right) \cdot \left( \left( {{C\; 3_{0}} + {C\;{3_{1} \cdot z^{- 1}}}} \right) \right)}{C\;{1_{1} \cdot C}\;{2_{1} \cdot C}\; 3_{1}{{\quad\quad} \cdot}}}\quad}{\quad{\left( \frac{1}{z} \right)^{3} + {\left\lbrack {{{\left( {{C\;{1_{0} \cdot C}\; 2_{1}} + {C\;{1_{1} \cdot C}\; 2_{0}}} \right) \cdot C}\; 3_{1}} + {C\;{1_{1} \cdot C}\;{2_{1} \cdot C}\; 3_{0}}} \right\rbrack \cdot \left( \frac{1}{z} \right)^{2}} + \frac{{{\left( {{C\;{1_{0} \cdot C}\; 2_{1}} + {C\;{1_{1} \cdot C}\; 2_{0}}} \right) \cdot C}\; 3_{0}} + {C\;{1_{0} \cdot C}\;{2_{0} \cdot C}\; 3_{1}}}{z} + {C\;{1_{0} \cdot C}\;{2_{0} \cdot C}\; 3_{0}}}}$The computation of the cumulative linear filter is preferably computedat a slow rate by the on-chip uP (or in some cases, by dedicatedhardware/fixed logic). The convolution and the algebraic equations areequivalent implementations.Note: The taps for the cumulative filter can be seen to be products ofthe filter responses. Since most of the coefficients are small and lessthan 1, the products are even smaller which can make some of thecalculated taps negligible. Using information about the expected rangesof the coefficients C1, C2, and C3, it is possible to determine whichones are not significant and these coefficients can be omitted from thehardware. This means that “Approximations” to the convolved transferfunctions can also be used. This can be particularly useful since eachtap (i.e., each coefficient) requires its own lookup table in thehardware for adjusting the residue or a delayed version of the residue.If a coefficient can be omitted, the look up table implementing thatcoefficient can be omitted. Convolution of multiple filters bydefinition expands the number of taps, and thus the ability to removecertain taps can greatly reduce the complexity of the system.

Exemplary Error Coefficients for Dither Subtraction

Dithering involves injecting a random signal (e.g., from an output of aDAC) to help remove spurs in the output spectrum. When dithering isused, in some cases, the injected signal is not precisely known becausethe dither signal is generated using a DAC, and is the dither signal isinjected in the analog side. Because the actual amplitude is notnecessarily well known enough, the dither signal is calibrated ormeasured so that it can be subtracted out properly.

FIG. 26 shows an exemplary hardware flow for dither subtraction andexemplary accumulation and decimation blocks, according to someembodiments of the disclosure. This example is applicable for pipelineADCs in general, and for pipeline ADCs used as sub-ADCs in timeinterleaved ADCs. The FIGURE shows a dither subtraction block, e.g.,dither_sub 2602 (for subtracting the dither signal that was previouslyinserted in the converter signal chain), DC accumulation/decimationblock 2604, and average magnitude accumulation/decimation block 2606.

Referring to the dither_sub 2602, the on-chip uP can provide signal 2608to enable different dither signal levels (also provided by the on-chipuP) to be selected through muxes using circuitry 2610. The signal 2608is also provided to perform correlation, using correlator 2612 tomeasure any dither DAC errors, as illustrated by the following series ofsteps implemented for a 7-bit Binary DAC for dither with 4 mostsignificant bits injected in FLASH/MDAC (which keeps from usingexcessive Error Correction Range) and with 3 least significant bitsinjected into MDAC only. The binary weighted DAC has each bit viewed as2 level DAC with separate correlations for each bit. To foreground orbackground calibrate the Dither DAC, the on-chip uP can force circuitry2610 to round robin or go through the dither DAC one bit at a time, andrun the LMS algorithm to minimize the RMS error (with the possibility toadd de-correlation for 2^(nd) and 3^(rd) order products of dither[2:0]for non-linear estimation).

In some embodiments, the dither_sub 2602 subtracts the (large) dithersignal which was injected in the front-end of the overall ADC. Assumingthe DAC which generated the dither signal is a binary DAC, eachcapacitor for generating each bit for generating a particular voltagelevel are weighted in a binary manner. For example, the MSB-1 bit wouldbe weighted ½ of the weight of the MSB bit. It is possible to correlatethe weight of each bit using a dither correlator. The estimate weightscan be determined independently for each bit of the dither DAC.

Further accumulation/decimation blocks are provided to collectmeasurements representative of the DC component of the output signal(using DC accumulation/decimation block 2604), and measurementsrepresentative of (using the magnitude |x| block and the averagemagnitude accumulation/decimation block 2606). The outputs from theaccumulation/decimation blocks can be provided to the on-chip uP forcalibration, debug, or testing purposes.

Example: Interleaving Offset Calibration

The average offset for each of the interleaved sub-ADCs may not bematched exactly, and the interleaving offset can be calibrated.

-   -   Two basic modes can be supported.        -   a. Average offset of all subADCs and drive mismatch to zero.            -   i. Equivalent to a DC coupled system. Preserves DC                content.        -   b. Independently drive the offset of each subADC to zero.    -   In both methods the correction is simply        -   a. subADC[sn]=subADC[sn]−dc_corr[sn]    -   DC Coupled Method        -   a. Use the subADC offset averaged over N samples to correct            offset            -   i. meas_dc[sn]=mean(subADC[sn]), every N samples        -   b. Correction term is based off of deltas between each            measured offset and the mean across all subADCs.        -   c. dc_corr[sn]+=mu*(meas_dc[sn]−mean(meas_dc))            -   i. The on-chip uP can compute this, or even perform                further averaging of the meas_dc[sn] data.    -   AC Coupled Method        -   a. dc_corr[sn]+=dc_corr[sn]+mu*(meas_dc[sn])            -   i. The on-chip uP can compute this, or even perform                further averaging of the meas_dc[sn] data.

In some embodiments, the reference ADC can be used to speed upconvergence of the calibration process (e.g., by almost 200×). Withoutthe reference ADC, many samples are used for the average to measure theoffset, especially when the signal is large. Using a reference ADC, thesignal content is removed, and the averaging can focus on the noise orvariations of the sub-ADCs. The above calculations are adjustedaccording to the following:

-   -   mean(subADC[sn]) has to average out the signal that looks noise        like.    -   Replace by mean(subADC[sn]−RefADC)    -   RefADC and the subADC sample at the same time instant so this        first order nulls the signal.

Example: Interleaving Gain Calibration

The gain for each of the interleaved sub-ADCs may not be matchedexactly, and the interleaving gain can be calibrated.

-   -   In both methods the correction is simply        -   a. subADC[sn]=subADC[sn]*gain_corr[sn]            -   i. Gain_corr placed in look-up tables used for IGE                calibration. Does not require a separate multiplier                (thereby saving area and power). The on-chip uP can                advantageously perform algebra/arithmetic to combine                this into a look-up table.        -   b. Use the magnitude of the subADC averaged over N samples            to correct offset (measured by taking the absolute value,            e.g., abs( ))            -   i. meas_mag[sn]=mean(abs(subADC[sn]))        -   c. One subADCs magnitude is used as a reference.            -   i. subADC_ref_mag        -   d. Correction term is based off of deltas between each            measured offset and the mean across all subADCs. The            correction term can be computed using the on-chip uP.            -   i. gain_corr[sn]+=mu*(meas_mag[sn]−subADC_ref_mag)

In some embodiments, the reference ADC can be used to speed upconvergence of the calibration process (e.g., by almost 200×). Withoutthe reference ADC, many samples are used for the average to measure theoffset, especially when the signal is large. Using a reference ADC, thesignal content is removed, and the averaging can focus on the noise orvariations of the sub-ADCs. The above calculations are adjustedaccording to the following:

-   -   mean(abs(subADC[sn])) has to average out the signal that looks        noise like.    -   Replace by mean(abs(subADC[sn])−abs(RefADC))    -   RefADC and the subADC sample at the same time instant so this        first order nulls the signal.

Example: Interleaving Skew Calibration

Sampling times for interleaved for each of the interleaved sub-ADCs maynot be matched exactly over time, and the interleaving skew can becalibrated. FIG. 27 illustrates sampling of adjacent sub-ADCs, accordingto some embodiments of the disclosure. S2 is the reference ADC in thispicture. Ideally times between S1,S2 and S2,S3 are equal. FIG. 28illustrates sampling of reference and adjacent sub-ADCs, according tosome embodiments of the disclosure. The reference ADC generally samplesdata at a lower rate but is generally guaranteed to sample along withall sub-ADCs over time. Cross-correlation can also be applied forinterleaving skew calibration. The cross-correlation of two signals canbe defined as:

${{AC}(\tau)} = {\frac{1}{N}{\sum\limits_{n = 0}^{n = {N - 1}}\;{{\sin\left( {{\omega*{nT}} + {\omega*\tau}} \right)}*{\sin\left( {\omega*{nT}} \right)}}}}$

For sufficiently large N and signals not around Fs/2 this reduces to

${{AC}(\tau)} = {\frac{1}{2N}{\sum\limits_{n = 0}^{n = {N - 1}}\;{\cos\left( {\omega*\tau} \right)}}}$

Term is proportional to the input frequency and the time delay. This canwork across one Nyquist (e.g., DC-5 GHz or 5 GHz-10 GHz) zone at a time.Tau=T_(s)+t_(mismatch). At Fs/2 we change 180 degrees between phases.Based on the cross-correlation and the measured mismatch, it is possibleto correct the timing of each sub-ADC by skewing the sample clock in theanalog domain. Error coefficients can be calculated by on-chip uP andfed back to the analog side for adjusting the sample clock. A number ofschemes can be used to find timing skew, and the on-chip uP canconfigure the circuitry to make the desired measurements and perform thedesired error coefficient updates.

In one example, cross correlation between adjacent sampling sub-ADCs canbe used to determine skew. The difference between any 2 sub-ADCs shouldbe zero. One sub-ADC is chosen as the timing reference. Equations forthe lag and lead measurements are as follows:

-   -   Ccorr_lag_meas=mean(ref_subADC*sub_adc_lag[sn])    -   Ccorr_lead_meas=mean(ref_subADC*sub_adc_lead[sn])    -   Thus—Tskew[sn]+=mu*(Ccorr_lag_meas−Ccorr_lead_meas), where Tskew        is computed by the on-chip uP and written back to the analog        side.

In another example, a reference ADC can be chosen as the timingreference. Equations for the measurements are as follows:

-   -   Ccorr_ref=mean(ref_ADC*ref_subADC)    -   Ccorr_2[sn]=mean(ref_ADC*sub_adc_lead[sn])    -   Thus—Tskew[sn]+=mu*(Ccorr_ref−Ccorr_2[sn]), where Tskew is        computed by the on-chip uP and written back to the analog side.

In some embodiments, one or both of the RefADC and subADCs can bereplaced by just the sign bit (e.g., +1 or −1) in any the aboveequations. For example:Ccorr_ref=mean(sign(ref_ADC)*sign(ref_subADC[sn]))

Reference ADC Enables More Nyquist Zones and Provides Faster CalibrationLoops

Generally, the reference ADC is of a lower resolution (very noisy),sometimes, when the main ADC takes a sample, the reference ADC alsosamples along with and in parallel with the main ADC. In embodimentswhere the main ADC has a plurality of time-interleaved sub-ADCs whichare operating in a pseudo-randomized sequence (i.e., thetime-interleaved sub-ADCs are randomly sampling the analog input), thereference ADC can be randomly sampling the analog input. A randomlysampling ADC means that the (instantaneous or any given) sampling periodcan vary or can be randomized so that the sampling frequency is spreadout across multiple frequencies or a range of frequencies, as related tospread spectrum clocking described herein). Advantageously, the randomlysampling reference ADC can avoid issues caused by periodicity in thesystem, etc.

In some cases, the reference ADC has a maximum sampling rate that isslower than the effective sampling rate of the main ADC (e.g., effectiverate of the time-interleaved sub-ADCs). The sampling rate of thereference ADC may be closer to the sampling rate of one of thetime-interleaved ADCs. When one of sub-ADCs in the main ADC is sampling,the reference ADC may not necessarily be sampling along with the one ADCthat is sampling since the sampling rate of the reference ADC is slowerthan the effective rate of the time-interleaved sub-ADCs. However, overtime, the reference ADC is expected to sample substantially the samenumber of times with each of the sub-ADCs in the main ADC.

In some cases, the reference ADC is a fast but noisy ADC (the faster thereference ADC is, the more information it can generate for thecalibration algorithms). To provide a fast ADC, it is possible toprovide a fast ADC (which can sample as fast as the main ADC), butdigitizes the data at a slower rate. The main ADC and the reference ADCgenerally do not sample at exactly the same time, but the sampling ofthe reference ADC and the sampling of the main ADC is done substantiallyclose together in time (e.g., 10-15 picoseconds apart). By design, thereference ADC can be guaranteed to sample just after the main ADC takesa sample, or the reference ADC can be guaranteed to sample just beforethe main ADC takes a sample. Ideally the two samples should equal, or atleast on average the two samples should be equal. The digital output ofthe reference ADC should be representative of the digital outputgenerated by the main ADC (or one of the sub-ADCs in the ADC that wassampling). Based on this assumption, calibration algorithms can run in amode that drives the main ADC to be equal to the reference ADC onaverage.

In some implementations of interleaved calibration, restrictions areimposed on what the input signal can be, e.g., that the input signal cannormally occupy 1 Nyquist zone. For an exemplary 10 GHz converter, theinput signal may then occupy from DC to 5 GHz, or 5 GHz to 10, but notboth. However, with a reference ADC sampling at the same time as themain ADC (instead of relying on one of the sub-ADCs as a reference, oruse only information from the main ADC to calibrate the ADC), theone-Nyquist zone limitation is no longer a restriction, and the inputcan occupy any frequency. Effectively, the reference ADC can allow theconverter to work across multiple Nyquist zones.

Another benefit of the reference ADC, as explained above, is the abilityto speed up the calibration loops. The reference ADC can be used as thereference so that less number of samples is needed to obtain the averageof the input signal. If you don't have a reference ADC, and you arecalibrating within the channels, you only unique information shows up at10 GHz (the sample rate of your converter). The faster the referenceADC, the faster the calibration algorithm can converge.

Generally speaking, many of the calibration schemes leverages randomsampling for best performance. Random sampling avoids issues with inputsignals that are harmonically related to the clock (e.g., Fs/2, Fs/4,Fs/8, etc.). For instance, with 8 sequentially interleaved ADCs eachsampling at Fs/8, each interleaved ADC would have a DC input. The DCoffset in the interleaved ADCs would be corrupted. The DC, Gain, andtiming information cannot be separated. Having the main ADC randomlysampling the input signal helps make the calibrations more robust fordifferent types of input signals. Furthermore, the randomly samplingreference converter helps to make sure any interference the referenceconverter causes to the main ADCs look more noise like and minimizes anydegradation in spurious-free dynamic range (SFDR).

On-chip uP can Control Error Coefficient Update Rate

In the many of the calibration processes described herein, μ or “mu” isa variable which can be used to change the rate of how quickly the errorcoefficients (e.g., dc_corr[sn]) are being updated. The effect of “mu”filters changes to the error coefficient according to a desirable stepsize set by the value of “mu”. The on-chip uP can be used to control“mu”, e.g., based on operating conditions (e.g., temperature changes,age, etc.). Advantageously, the “mu” can be optimized for a given time.

On-chip uP as a Controller

One advantage of an on-chip uP is its ability to assert start signals tocorrelators of calibration blocks to initiate averaging and correlationof samples. Once the correlator has completed averaging and correlatinga specified number of samples (e.g., can be specified by the on-chipuP), the correlator can assert an interrupt signal to the on-chip uP toindicate the data for calibration is ready to be read by the on-chip uP.

Overview of Technical Advantages of the on-Chip uP

Providing an on-chip uP (as opposed to using solely specialized digitalhardware) is the ability to shorten design and/or test time by movinghardware resistor-transistor logic (RTL) into software code that can beexecuted by the on-chip uP. The on-chip uP can potentially reduce powerand/or area by moving some processing to the on-chip uP (which operatesin a lower sample rate domain). While the on-chip uP is clocked fast,the on-chip uP can further reduce power by operating in a low powerstate when the on-chip uP is not needed. Furthermore, the on-chip uP canreduce dedicated hardware. Precision requirements are easier to meetwith an on-chip uP because, e.g., 32-bit integers and single-precisionfloating point re available. The need to optimize math is reduced. Theon-chip uP provides a great amount of flexibility to improvetrim/calibration on silicon. In some embodiments, firmware can beupdated or selected using fuses, which can provide the ability to tailorparts for market segments or customers. The on-chip uP can possiblyspeed up test time by providing on-chip computation.

Overview of the on-chip uP (Subsystem) and Connections of the on-chip uP

FIG. 29 shows an exemplary on-chip uP and connections of the on-chip uPto communicate with the rest of the chip, according to some embodimentsof the disclosure. The on-chip uP 2902 (subsystem) can include a digitalsignals processor 2904, or some suitable processor which can executeinstructions to carry out data processing such as arithmetic logic, etc.The instructions and data associated with the data processing can bestored in internal memory 2906. Generally speaking, the on-chip uP 2902can write and/or read registers 2908 which can store a variety of dataincluding error coefficients, measured error, states of the on-chip uP2902, parameters for calibration processes, states of the calibrationprocesses, etc. An address decode block can be used to map memoryaddresses used by the processor to addresses used by the registers.Usually, measurements can readable by the on-chip uP 2908 throughregisters. A serial peripheral interface (or some other suitableinterface) can provide external access to the on-chip uP 2902 (e.g.,such as access to memory 2906). The interface can also provide externalaccess to the memor(-ies) and/or register(s) to which the on-chip uP2902 can access. Furthermore, the interface can also provide externalaccess to memor(-ies) and/or register(s) to which the on-chip uP 2902 donot have access.

An interrupt arbiter 2910 can include circuitry which can generate anIRQ (an interrupt signal) from one or more DONE signals (signalindicating measurements are ready, e.g., from a correlator) and provideIRQ to the on-chip uP 2902 to signal to the on-chip uP that themeasurements are ready. Advantageously, the interrupt arbiter can reduceinterrupt count from the hardware to the on-chip uP 2902. For instance,eight DONE signals from sub-ADC calibration blocks can be reduced toone. In another instance, eight DONE signals from interleavingmeasurements can be reduced to one. This interrupt arbiter can simplifysoftware coding and reduces simulation set. Furthermore, the interruptarbiter can lower context switching overhead/power.

The ADC Capture first in first out (FIFO) buffer 2912 accessible by theon-chip uP 2902 allows capture of ADC data or debug information.

In some embodiments, a random access memory (RAM) 2914 or some othersuitable memory element is accessible (read and/or write) by the on-chipuP 2902 as spare memory for storing data and/or instructions. Forinstance, parameters and/or instructions for the calibration algorithmscan be loaded onto RAM 2914 and the on-chip uP 2902 can executecalibration algorithms using on the parameters and/or instructions(thereby allowing calibration algorithms to be tuned/changed on thefly).

One or more sensors can provide sensor measurements to the on-chip uP2902 to improve calibration algorithms, including a temperature sensor2916. In one example, the temperature measurement can enable rates forupdating error coefficients to change accordingly (e.g., big changes intemperature may suggest error coefficients should be updated faster). Inanother example, temperature measurement can be used to select a set oferror coefficients to be used.

The following describes an exemplary sequence of operation of theon-chip uP, such as on-chip uP 2902:

-   1. The processor issues a START command (e.g., using a START signal,    or transmitting a signal to set a START bit in register to a state    that indicates “START”) to one or more dedicated measurement    hardware to capture measurements. Examples include correlators, DC    offset accumulation/decimation blocks, average magnitude    accumulation/decimation blocks. The register of the dedicated    measurement hardware can include a separate ENABLE Bit, so the    on-chip uP can enable only what it needs. Clocks can be gated off to    save power if not enabled.-   2. Each dedicated measurement hardware, or groups of dedicated    measurement hardware (e.g., 8 sub-ADCs) can return a DONE signal    once the measurement is complete.-   3. The signals from the dedicated measurement hardware, or groups of    dedicated measurement hardware can be synchronized in hardware    (e.g., using interrupt arbiter) to provide a reduced set of    interrupts to the on-chip uP.-   4. On interrupt, memory mapped coefficients are read from the    hardware. The memory mapped coefficients can be placed in the    (32-bit) registers for speed.-   5. The (32-bit) data is read back, and is either further averaged in    the on-chip uP or is immediately used for adaptive updates. Adaptive    updates can occur using the read back measurement data, using LMS or    any suitable method, e.g., Coef=Coef+μ*step-   6. These updates are the state variables or “memory” in the system.    The coefficients are adjusted when needed, but is generally not    cleared unless the on-chip uP is reset. If one variable is messed up    the performance could suffer until background calibration    reconverge. In some cases, software redundancy can be provided to    improve reliability. For example, the redundancy function can    enforce rules on the coefficients, e.g., 2 of 3 memory locations    must agree for the update to occur.-   7. The adapted coefficients are mapped to coefficients to drive the    high speed hardware. Look up tables (e.g., muxes) and other values    are calculated by the on-chip uP for the high-speed hardware and    written back to the 32-bit registers.-   8. The on-chip uP can, if desired, signals a new START and repeats    the process. The on-chip uP can also go into a low power state until    conditions indicate the on-chip uP should signal a new START.

Besides implementing calibration, the on-chip uP (serving as thecontroller of the overall system), can also provide functionality indebug mode. For instance, the on-chip uP can use a capture FIFO toobtain ADC data from all sub-ADCs and reference ADCs in any debug mode.Furthermore, the on-chip uP can allow other calibrations to be done in ablock processing manner. While the on-chip uP can have slowerconvergence, the on-chip uP offers huge flexibility. Moreover, theon-chip uP can generate hardware Error Waveform and integralnon-linearity curves, which can be used for factory/foreground trim ifan input can be provided.

Besides reducing design and/or test time by moving processing on chip,having the same firmware code used during the design, test, and productphases can promote code reuse.

Besides providing arithmetic calculations, the on-chip uP can providedigital signal processing functions such as discrete Fourier transformsand fast Fourier transforms that can enable better estimation ofspectral content (of the input and/or output), which can in turn allowbetter tuning for some calibration algorithms.

Examples Illustrating Microprocessor-Assisted Calibration forAnalog-to-digital Converter

Example 1 is a randomized time-interleaved analog-to-digital convertercomprising: two or more analog-to-digital converters (ADCs) forsampling, interleaved in time according to a pseudo-randomized sequence,an analog input signal and generating respective digital output signals,a microprocessor on-chip with the two or more analog-to-digitalconverters for executing instructions stored on-chip configured toassist the randomized time-interleaved analog-to-digital converter,first circuitry (can be digital or analog) for adjusting the two or moreanalog-to-digital converters, and second circuitry (dedicatedspecialized circuitry, or high speed circuitry) for processing signalsin the two or more analog-to-digital converters to generate and recordmeasurements of the signals in an on-chip memory, and making themeasurements accessible to the microprocessor at a rate slower than aclock rate of the microprocessor.

When interleaved in time, these two or more ADCs can effectively samplethe analog input faster than the rate of just one ADC. In some cases,the randomized time-interleaved analog-to-digital converter can includethree or more ADCs (e.g., 4 sub-ADCs, 8 sub-ADCs, etc.). In someembodiments, the second circuitry is clocked at the rate of one ADC.Since the microprocessor generally can run at a much slower rate thanone ADC, and the microprocessor can be limited to how fast and how muchdata the microprocessor can process. The second circuitry is provided toreduce the amount of data (i.e., by converting raw data tomeasurements), and reduce the rate of the data so that it is at a ratelow enough for the data/measurements to be processed by themicroprocessor. This second circuitry is in contrast to a capture memory(e.g., a first in first out memory) for capturing raw data of the ADCs,because the second circuitry processes the data to generate measurementsfor the microprocessor. In some embodiments, a capture memory can beimplemented in addition to the second circuitry, e.g., for debuggingpurposes. The microprocessor can be provided on a same semiconductorsubstrate as the two or more analog-to-digital converters.

In some cases, the first circuitry comprises calibration circuitry forcorrecting signals in a digital domain. In some cases, the firstcircuitry comprises calibration circuitry for compensating errors of thetwo or more analog-to-digital converters in an analog domain.

In Example 2, the randomized time-interleaved analog-to-digitalconverter of Example 1 can optionally include a clock generator forgenerating a clock signal for the microprocessor to provide spreadspectrum clocking, wherein the clock signal has on average a particularfrequency but an instantaneous period of the clock signal is randomized.

In Example 3, the randomized time-interleaved analog-to-digitalconverter of Example 2 can optionally include the clock generatorgenerating clock signal(s) for running one or more of the following: anyone or more of the two or more analog-to-digital converters, and areference analog-to-digital converter sampling in parallel with the twoor more analog-to-digital converters.

In Example 4, the randomized time-interleaved analog-to-digitalconverter of any one of Examples 1-3 can optionally include the secondcircuitry for processing signals in the two or more analog-to-digitalconverters comprises one or more of the following: correlator logic,accumulation logic, decimation logic, absolute value logic, and squaringlogic.

In Example 5, the randomized time-interleaved analog-to-digitalconverter of any one of Examples 1-4 can optionally include the firstcircuitry comprising registers for storing coefficients, said registersaccessible by one or more of the following: any one or more of the twoor more analog-to-digital converters, the second circuitry, and areference analog-to-digital converter sampling in along with the two ormore analog-to-digital converters.

In Example 6, the randomized time-interleaved analog-to-digitalconverter of any one of Examples 1-5 can optionally comprise wherein theinstructions includes a code portion selected from a plurality of codeportions for different applications, wherein the code portion isselected using one or more of the following: one or more fuses,non-volatile memory, and one or more input pins. In someimplementations, the instructions are generated from code that ispartitioned for different applications. Code portions can encompass codepartition, code segment, etc. Depending on the application (or product),different code portion or sets of code portions can be selected forgenerating instructions to be executed by the microprocessor. The resultis a highly flexible system.

In Example 7, the randomized time-interleaved analog-to-digitalconverter of Example 6 can optionally include the code portionscorresponding to different calibration sequences or differentcalibration schemes for the randomized time-interleavedanalog-to-digital converter.

In some cases, the instructions are loaded and stored in volatile memoryon chip by a user via an interface. In some cases, the microprocessorincludes an interface for changing parameters of the randomizedtime-interleaved analog-to-digital converter. The parameters can includeone or more of the following: modes of operation, whether ananalog-to-digital converter is used, resolution of the analog-to-digitalconverter, and dynamic range of the analog-to-digital converter. In somecases, includes an interface for accessing error logs or abnormal eventsof the randomized time-interleaved analog-to-digital converter.

In Example 8, the randomized time-interleaved analog-to-digitalconverter of any one or Examples 1-7 can optionally include themicroprocessor polling the on-chip memory for measurements. The on-chipmemory can encompass any one or more of the following: on-chip storagecircuitry or on-chip storage elements, on-chip memory hardware, on-chipmemory circuitry, on-chip registers for storing data or values, etc.

In Example 9, the randomized time-interleaved analog-to-digitalconverter of any one of Examples 1-8 can optionally include themicroprocessor asserting a start signal to the second circuitry toinitiate processing of signals in the two or more analog-to-digitalconverters by the second circuitry, and the second circuitrytransmitting an interrupt to the microprocessor to signal to themicroprocessor that the measurements are ready.

In Example 10, the randomized time-interleaved analog-to-digitalconverter of any one of Examples 1-9 can optionally include adigital-to-analog converter (DAC) for generating bits of a random signalbeing injected into a first one of the two or more analog-to-digitalconverters; and a subtraction circuit for subtracting the injectedrandom signal, the subtraction circuit comprising two registers per eachbit of the digital-to-analog converter, wherein values stored in the tworegisters are selectable by a respective bit of the random signal forsubtracting the random signal. The second circuitry can comprise aone-bit correlator and an accumulator block for estimating errors of aparticular bit in the dither digital-to-analog converter, and themicroprocessor can update values stored in the two registers per eachbit based on the estimated errors. In some cases, this digital-to-analogconverter is a dither digital-to-analog converter, and the random signalis a dither signal being injected into an ADC. The subtraction circuitwould aim to subtract the dither signal completely. This system treatsthe DAC as a sum of multiple two-level DACs, and tries to find the errorfor each two-level DAC separately/independently. A single set of theone-bit correlator and accumulator block can be provided in the systemand the error estimation can be performed bit by bit (one by one). Insome cases, multiple sets of the one-bit correlator and accumulatorblock can be provided so that the multiple bits can be correlated at atime (in parallel).

In Example 11, the randomized time-interleaved analog-to-digitalconverter of Example 10 can optionally include the ditherdigital-to-analog converter being configured to toggle between twovalues corresponding to a bit under calibration every clock cycle, andrandomly toggle between two values for other bits on a divide by twoclock, to allow an error of the bit under calibration to be measured bythe one-bit correlator and the accumulator block.

Example 12 is a method for assisting a randomized time-interleavedanalog-to-digital converter comprising two or more analog-to-digitalconverters for sampling, interleaved in time according to apseudo-randomized sequence, an analog input signal and generatingrespective digital output signals. The method comprises executing, by amicroprocessor on chip with the two or more analog-to-digitalconverters, instructions stored on-chip configured to assist therandomized time-interleaved analog-to-digital converter, processing, bydedicated circuitry, signals in the two or more analog-to-digitalconverters, recording, by the dedicated circuitry, measurements of thesignals in a memory accessible to the on-chip microprocessor at a rateslower than a clock rate of the microprocessor, and writing, by theon-chip microprocessor, coefficients to calibration circuitry foradjusting the two or more analog-to-digital converters, wherein thecoefficients are determined by the on-chip microprocessor based on themeasurements and the instructions executable by the on-chipmicroprocessor.

In Example 13, the method of Example 12 can optionally includedetecting, by the on-chip microprocessor, condition(s) in the randomizedtime-interleaved analog-to-digital converter based on measurementsrecorded by the dedicated circuitry, and adjusting, by the on-chipmicroprocessor, one or more parts of an adaptation algorithm based onthe condition(s) being detected. An example of a condition isoverranging (sometimes referred to as clipping due to the input signalbeing too large). When such a condition is detected, the on-chipmicroprocessor can halt the updating or writing of error coefficients tothe calibration circuitry (e.g., on-chip memory that is accessible bythe randomized time-interleaved ADC)

In Example 14, the method of Examples 12 or 13 can optionally includeensuring, by the on-chip microprocessor, error coefficient(s) beingwritten to the calibration circuitry do not go beyond a suitable rangeor do meet one or more expected characteristics. This can involvechecking whether the error coefficient is within the suitable range orwhether the error coefficient is outside of the suitable range. This caninvolve checking the error coefficient against one or more expectedcharacteristics (e.g., a coefficient cannot be zero, a coefficientcannot be negative, a coefficient cannot be more than N number ofstandard deviations from a mean, a coefficient cannot be an outlierbased on a certain statistical probability distribution, etc.).

In Example 15, the method of any one of Examples 12-14 can optionallyinclude adjusting, by the on-chip microprocessor, the dedicatedcircuitry based on measurements of a state of the randomizedtime-interleaved analog-to-digital converter, wherein adjusting thesecond circuitry comprises adjusting a number of samples being used foraveraging in an accumulator or a term used for dividing an accumulatedvalue when computing an average.

In Example 16, the method of any one of Examples 12-15 can optionallyinclude executing, by the on-chip microprocessor, an adaptationalgorithm for updating error coefficients being written to thecalibration circuitry, adjusting, by the on-chip microprocessor, a rateof the adaptation algorithm based on a state of the randomizedtime-interleaved analog-to-digital converter.

In Example 17, the method of any one of Examples 12-16 can optionallyinclude determining whether an input frequency is of a certain range,and tuning a number of dithering levels of the randomizedtime-interleaved converter in response to determining the inputfrequency is of the certain range.

Example 18 is a system on-chip with a time-interleaved analog-to-digitalconverter for assisting the time-interleaved analog-to-digitalconverter. The system comprises a microprocessor comprising a digitalsignal processor for executing instructions for carrying out arithmeticlogic associated with calibration of the time-interleavedanalog-to-digital converter, dedicated circuitry for (processing rawdata and) making measurements of the time-interleaved analog-to-digitalconverter, internal memory for storing instructions and data associatedwith the arithmetic logic, registers for storing data for assisting thetime-interleaved analog-to-digital converter, wherein the registers areaccessible to the microprocessor, the dedicated circuitry, and thetime-interleaved analog-to-digital converter, and an interrupt arbiterincluding circuitry for generating an interrupt signal to themicroprocessor in response to receiving one or more signals fromdedicated circuitry indicating measurements are ready.

In Example 19, the system of Example 18 can optionally include theregisters storing one or more of the following: error coefficients,measured error, states of the microprocessor, parameters for calibrationprocesses, and states of the calibration processes.

In Example 20, the system of Example 18 or 19, can optionally includeone or more sensors for providing sensor measurements to themicroprocessor to change one or more rates for updating errorcoefficients associated with the calibration according to the sensormeasurements.

Example 21 is an apparatus for performing any one of the methods inExamples 12-17.

Examples Illustrating Randomly Sampling Reference ADC for Calibration

Example 101 is a randomized interleaved analog-to-digital convertercomprising: two or more analog-to-digital converters to sample,interleaved in time according to a pseudo-randomized sequence, an analoginput of the randomized interleaved analog-to-digital converter andgenerate respective digital outputs, a digital combiner to combine therespective digital outputs of the two or more analog-to-digitalconverters to generate a digital output of the randomized interleavedanalog-to-digital converter based on the pseudo-randomized sequence, areference analog-to-digital converter for randomly sampling the analoginput and generating reference digital outputs that are representativeof the digital outputs of the two or more analog-to-digital converters,and calibration logic for measuring interleaving errors of the two-oranalog-to-digital converters based on the respective digital outputs ofthe two-or more analog-to-digital converters and the reference digitaloutputs. Note that the reference ADC may not sample the analog inputeach time one of the two-or-more analog to digital converters issampling the input. When the reference ADC is sampling, the referenceADC would sample along with a particular one of the two or more ADCsthat is selected to sample the input so that a reference digital outputgenerated by the reference ADC would be representative or wouldrepresent the digital output generated by that particular selected ADC.In some cases, the reference ADC samples just after that particularselected ADC (by a fixed delay, but very small delay). In some cases,the reference ADC samples ahead of that particular selected ADC (by afixed lead, but very small lead). The difference in sampling time issufficiently small to ensure that the reference digital output is stillrepresentative of the digital output generated by the particularselected ADC (as such the reference ADC can be considered to sample atsubstantially the same time as the particular selected ADC). In somecases, over time, the number of times the reference ADC samples alongwith a particular ADC is roughly the same across the two or more ADCs(even though the reference ADC randomly samples the analog input).

In Example 102, the randomized interleaved analog-to-digital converterof Example 101 can optionally include that each time the referenceanalog-to-digital converter samples the analog input, the referenceanalog-to-digital converter samples the analog-input along with one ofthe analog-to-digital converters that is sampling the analog input. Thereference ADC samples the analog input in parallel with one of theanalog-to-digital converters that is sampling the analog input, thus thereference ADC serves as additional path, or a path parallel to the twoor more ADCs.

In Example 103, the randomized interleaved analog-to-digital converterof Example 101 or 102 can optionally include the referenceanalog-to-digital converter having (instantaneous) sampling periodswhich are randomized.

In Example 104, the randomized interleaved analog-to-digital converterof any one of Examples 101-103 can optionally include a clock generatorfor generating a clock signal having a range of clock periods for thereference analog-to-digital converter to randomly sample the analoginput.

In Example 105, the randomized interleaved analog-to-digital converterof any one of Examples 101-104 can optionally include one or more clockdivider circuits that output an edge of a clock signal for driving thereference analog-to-digital converter to sample the analog input forevery X number of clock cycles of an input clock, and a randomizationengine to randomize X used by the one or more clock divider circuits.

In Example 106, the randomized interleaved analog-to-digital converterof any one of Examples 101-105 can optionally include a first resolutionof any one of the two or more analog-to-digital converters is higherthan a second resolution of the reference analog-to-digital converter.

In Example 107, the randomized interleaved analog-to-digital converterof any one of Examples 101-106 can optionally include the referenceanalog-to-digital converter serving as an additional signal path forconverting the analog input signal in parallel with the two or moreanalog-to-digital converters.

Example 108 is a method for calibrating a randomized interleavedanalog-to-digital converter comprising: generating, by a clockgenerator, first clock signals for controlling two or moreanalog-to-digital converters of the randomized time-interleavedanalog-to-digital converter to sample, interleaved in time according toa pseudo-randomized sequence, an analog input of the randomizedtime-interleaved analog-to-digital converter; generating, by the clockgenerator, a second clock signal for controlling a referenceanalog-to-digital converter for randomly sampling the analog input,wherein, when the reference analog-to-digital converter samples theanalog input, one of the two or more analog-to-digital converters isalso sampling the analog input at substantially the same time,processing respective digital outputs of the two or moreanalog-to-digital converters and digital outputs of the referenceanalog-to-digital converter over a period of time to generatemeasurements, determining interleaving errors associated with the two ormore analog-to-digital converters based on the measurements. As notedbefore, depending on the implementation, the reference ADC can samplealong with a particular one of the two or more ADC selected to samplethe analog input with a (small) constant time delay (or in some casesthe particular one of the two or more ADCs selected to sample the analoginput lags behind the reference ADC).

In Example 109, the method of Example 108 can optionally includeprocessing respective digital outputs of the two or moreanalog-to-digital converters and digital outputs of the referenceanalog-to-digital converter to generate measurements comprising for eachone of the two or more analog-to-digital converters, determining a meanof differences between digital outputs of a particular analog-to-digitalconverter and corresponding digital outputs of the referenceanalog-to-digital converter generated when the referenceanalog-to-digital converter is sampling along the particularanalog-to-digital converter.

In Example 110, the method of Example 109 can optionally includedetermining interleaving errors comprising updating an offset correctionterm for the particular analog-to-digital converter based on the mean.

In Example 111, the method of Example 108 or 109 can optionally includeprocessing respective digital outputs of the two or moreanalog-to-digital converters and digital outputs of the referenceanalog-to-digital converter to generate measurements comprising for eachone of the two or more analog-to-digital converters, determining a meanof differences between magnitudes of digital outputs of a particularanalog-to-digital converter and magnitudes of corresponding digitaloutputs of the reference analog-to-digital converter generated when thereference analog-to-digital converter is sampling along the particularanalog-to-digital converter.

In Example 112, the method of Example 111 can optionally includedetermining interleaving errors comprising updating an interleaving gaincorrection term for the particular analog-to-digital converter based onthe mean.

In Example 113, the method of any one of Examples 108-112 can optionallyinclude processing respective digital outputs of the two or moreanalog-to-digital converters and digital outputs of the referenceanalog-to-digital converter over a period of time to generatemeasurements comprising for each one of the two or moreanalog-to-digital converters, determining a cross correlation of a firstsignal representing digital outputs of a particular analog-to-digitalconverter and a second signal representing digital outputs of thereference analog-to-digital converter generated when the referenceanalog-to-digital converter is sampling along the particularanalog-to-digital converter.

In Example 114, the method of Example 113 can optionally includedetermining interleaving errors comprising updating an interleaving skewcorrection term for the particular analog-to-digital converter based onthe cross correlation of the first signal and the second signal.

In Example 115, the method of Example 113 or 114 can optionally includethe digital outputs of the particular analog-to-digital converter andthe digital outputs of the reference analog-to-digital converter arerepresented by a single bit. In some cases, the single bit is a sign bitfor a bi-polar converter.

Example 116 is a randomized converter system on a single chip forconverting an analog input to a digital output. The system comprises twoor more analog-to-digital converters to sample, interleaved in timeaccording to a pseudo-randomized sequence, the analog input of therandomized converter system and generate respective digital outputs, areference analog-to-digital converter for sampling the analog inputalong with one of the two or more analog-to-digital converters at randomand generating reference digital outputs, dedicated logic for recordingmeasurements of digital outputs of the two or more analog-to-digitalconverters and reference digital outputs of the referenceanalog-to-digital converter, and an on-chip microprocessor for assistingthe randomized converter system based on the measurements.

In Example 117, the randomized converter system of Example 116 canoptionally include a clock generator for generating clock signals to thetwo or more analog-to-digital converters to sample, interleaved in timeaccording to the pseudo-randomized sequence, and a clock signal to thereference analog-to-digital converter for randomly sampling the analoginput.

In Example 118, the randomized converter system of Example 117 canoptionally include the clock generator further generating a spreadspectrum clock signal for clocking the on-chip microprocessor, whereininstantaneous period of the spread spectrum clock signal is randomized.

In Example 119, the randomized converter system of any one of Examples116-118 can optionally include the on-chip microprocessor executinginstructions for computing one or more of the following: interleavingoffset correction term (for any one of the two or more ADCs);interleaving gain correction term (for any one of the two or more ADCs),interleaving skew correction term (for any one of the two or more ADCs),frequency response (e.g., transfer function of any one of the two ormore ADCs), and linearity of any one of the two or moreanalog-to-digital converters.

In Example 120, the randomized converter system of any one of Examples116-119, wherein the reference analog-to-digital converter and the twoor more analog-to-digital converters are each sampling the analog inputaccording to randomized periods.

In Example 121, the randomized converter system can include means forperforming any one of the methods in Examples 108-115.

Examples Illustrating Efficient Calibration of Errors in Multi-stageAnalog-to-digital Converter

Example 1001 is a multi-stage analog-to-digital converter with digitallyassisted calibration. The multi-stage analog-to-digital convertercomprises: (A) a plurality of analog-to-digital converter stages incascade, each analog-to-digital converter stage for generating arespective output code and a respective amplified output residue signal;(B) digital correction logic for each analog-to-digital converter stagecomprising: (1) a dedicated memory element for storing correction terms,(2) a multiplexer selecting one of the correction terms in the dedicatedmemory element based on the respective output code, and (3) an adder (orequivalent circuitry) for correcting an error of the multi-stageanalog-to-digital converter based on the selected correction term; and(C) digital circuitry on-chip with the plurality of analog-to-digitalconverter stages for computing the correction terms in the dedicatedmemory elements, wherein computing correction terms used for a givenanalog-to-digital converter stage takes into account an error term fromone or more earlier analog-to-digital converter stage. This example canbe beneficial for correcting errors in the transfer function(s) of themulti-stage analog-to-digital converter. These errors can encompass gainerrors, linearity errors, etc. The correction terms can replace a signalin the signal chain of the multi-stage analog-to-digital converter tochange the transfer function of interest. The correction terms, in somecases, can be added to a signal in the signal chain of the multi-stageanalog-to-digital converter to change the transfer function of interest.

In Example 1002, the multi-stage analog-to-digital converter of Example1001 can optionally include the adder adding the correction term to asum of the respective output code multiplied by a predetermined weightand the respective amplified output residue signal. An example of thisadder function is illustrated in FIG. 25 in stg_cal 2504.

In Example 1003, the multi-stage analog-to-digital converter of Example1001 or 1002 can optionally include the digital circuitry being amicroprocessor on-chip with the plurality of analog-to-digital converterstages configured to execute instructions to compute the correctionterms.

In Example 1004, the multi-stage analog-to-digital converter of any oneof Examples 1001-1003 can optionally include the correction term beingan additive correction term.

In Example 1005, the multi-stage analog-to-digital converter of any oneof Examples 1001-1004 can optionally include the plurality ofanalog-to-digital converter stages comprising a first stage and a secondstage following the first stage, and computing correction terms for thesecond stage comprising computing a first cumulative gain term whichincludes an interstage gain error of the first stage and an interstagegain error of the second stage.

In some cases, the multi-stage analog-to-digital converter canoptionally include the plurality of analog-to-digital converter stagesfurther comprising a third stage following the second stage (or evenmore stages), and computing correction terms for the third stagecomprising computing a second cumulative gain term which includes theinterstage gain error of the first stage, the interstage gain error ofthe second stage, and an interstage gain error of the third stage.Phrased differently, correction terms in subsequent stages takes intoaccount the interstage gain error of earlier stages.

In Example 1006, the multi-stage analog-to-digital converter of any oneof Examples 1001-1005 can optionally include computing correction termscomprising determining a gain correction term for the givenanalog-to-digital converter stage, determining a capacitor error termper output code of the given analog-to-digital converter stage, andadding each capacitor error term by the gain correction term multipliedby an output code to which the capacitor error term corresponds toobtain the correction terms selectable by the output codes.

In Example 1007, the multi-stage analog-to-digital converter of any oneof Examples 1001-1006 can optionally include computing correction termscomprising determining a gain correction term for the givenanalog-to-digital converter stage, determining a linearity error termper output code of the given analog-to-digital converter stage, addingeach linearity error term by the gain correction term multiplied by anoutput code to which the linearity error term corresponds to obtain thecorrection terms selectable by the output codes.

In Example 1008, the multi-stage analog-to-digital converter of any oneof Examples 1001-1007 can optionally include for each analog-to-digitalconverter stage, the multi-stage analog-to-digital converter furthercomprising a further dedicated memory element for storing furthercorrection terms, a further multiplexer selecting one of the furthercorrection terms in the further dedicated memory element based on adelayed version of the respective output code. Correcting the error ofthe multi-stage analog-to-digital converter based on the selectedcorrection term by the adder is further based on the selected furthercorrection term. For instance, correcting the error can include summingthe selected correction term and the selected further correction term toobtain a final correction term to be used by the adder.

In Example 1009, the multi-stage analog-to-digital converter of any oneof Examples 1001-1008 can optionally include the plurality ofanalog-to-digital converter stages comprising a first stage and a secondstage following the first stage, and computing correction terms for thesecond stage comprising computing a first cumulative linear filter whichincludes a linear filter corresponding to the first stage and a linearfilter corresponding to the second stage.

In Example 10, the multi-stage analog-to-digital converter of Example1009 can optionally include computing the first cumulative linear filtercomprising computing a convolution of taps of the linear filtercorresponding to the first stage and taps of the linear filtercorresponding to the second stage. In some cases, the plurality ofanalog-to-digital converter stages further comprises a third stagefollowing the second stage (or even further subsequent stages), andcomputing correction terms for the third stage comprises computing asecond cumulative linear filter which includes the linear filtercorresponding to the first stage, the linear filter corresponding to thesecond stage, and a linear filter corresponding to the third stage.Phrased differently, correction terms for subsequent stages takes intoaccount linear filters of earlier stages.

Example 1011 is a digitally assisted method for calibrating amulti-stage analog-to-digital converter comprising: measuring, bydedicated circuitry, errors in a plurality of analog-to-digitalconverter stages in cascade, wherein the analog-to-digital converterstages generate respective output codes and respective residue signals,computing, by digital circuitry on-chip with the plurality ofanalog-to-digital converter stages, correction terms to be used forcorrecting residue signals of the analog-to-digital converter stagesbased on the measured errors, wherein computing correction terms usedfor a given analog-to-digital converter stage takes into account anerror measured for one or more earlier analog-to-digital converterstage, writing, by the digital circuitry, the correction terms toseparate look up tables provided for each residue signal to becorrected, wherein each look up table is indexed by output codes of arespective analog-to-digital converter stage. In some cases, the digitalcircuitry comprises an on-chip microprocessor.

In Example 1012, the digitally assisted method of Example 1011 canoptionally include errors measured by the dedicated circuitry comprisinginterstage gain errors of the analog-to-digital converter stages.

In Example 1013, the digitally assisted method of Example 1012 canoptionally include measuring the interstage gain errors comprising:injecting a random signal to a particular analog-to-digital converterstage, and removing the random signal based on a previously determinedgain of the particular analog-to-digital converter stage to measure aninterstage gain error of the particular analog-to-digital converterstage.

In Example 1014, the digitally assisted method of Example 1013, canoptionally include the random signal being a two-level pseudo-randomsignal.

In Example 1015, the digitally assisted method of Example 1014 canoptionally include correlating, by the dedicated circuitry comprisingcorrelator circuitry, the random signal with an error signal left behindafter the random signal is removed.

In Example 1016, the digitally assisted method of Example 1015, canoptionally include reading, by the digital circuitry, correlationmeasurements made by the dedicated circuitry, and updating theinterstage gain error of the particular analog-to-digital converterstage based on the correlation measurements and a predetermined timeconstant.

In Example 1017, the digitally assisted method of any one of Examples1011-1016, wherein computing correction terms used for the given stagecomprises multiplying an interstage gain error term for the given stageand one or more interstage gain error terms from the one or more earlieranalog-to-digital converter stages.

In Example 1018, the digitally assisted method of any one of Examples1011-1017, wherein computing correction terms used for the given stagecomprises combining linear filter for the given stage and linearfilter(s) of the one or more earlier analog-to-digital converter stages.

In Example 1019, the digitally assisted method of any one of Examples1011-1018, wherein computing correction terms comprises: determining again correction term for the given analog-to-digital converter stage,determining a capacitor error term per output code of the givenanalog-to-digital converter stage, and adding each capacitor error termby the gain correction term multiplied by an output code to which thecapacitor error term corresponds to obtain the correction termsselectable by the output codes.

Example 1020 is an apparatus comprising: a plurality of cascadedanalog-to-digital converting means for generating respective outputcodes and respective residue signals, dedicated circuitry means formeasuring errors in the plurality of analog-to-digital converter means,separate storage means provided for each residue signal to be corrected,each storage means for storing correction terms selectable by arespective output code for correcting a respective residue signal,adding means for correcting respective residue signals based on selectedcorrection terms, and digital circuitry means on-chip with the pluralityof analog-to-digital converter for updating correction terms in theseparate storage means based on the measured errors, wherein updatingthe correction terms used for a given analog-to-digital converter stagetakes into account an error measured for one or more earlieranalog-to-digital converter stage. The digital circuitry means caninclude an on-chip microprocessor for executing instructions to updatethe correction terms.

In some cases, updating correction terms used for the given stagecomprises multiplying an interstage gain error term for the given stageand one or more interstage gain error terms from the one or more earlieranalog-to-digital converter stages. In some cases, updating correctionterms used for the given stage comprises combining linear filter for thegiven stage and linear filter(s) of the one or more earlieranalog-to-digital converter stages.

In Example 1021, the apparatus can include means for performing any oneof the methods in Examples 1011-1019.

Variations and Implementations

The present disclosure describes many embodiments related toanalog-to-digital converters (ADCs), but it is envisioned by thedisclosure that the embodiments are applicable to other converters,e.g., digital to analog converters, especially converters which canprovide digital circuitry and/or a microprocessor on the same substrate.Furthermore, the embodiments disclosed herein are also applicable to avertically integrated converter and processor on different sides or ondifferent layers of a vertically integrated circuit with athrough-silicon via (TSV) connecting them. In some embodiments, theon-chip uP is provided with the same package as the ADC, but notnecessarily on the same semiconductor substrate. Moreover, theembodiments disclosed herein can have on-chip memory and/or on-boardmemory for supporting the described functions.

Note that particular embodiments of the present disclosure may bereadily included in a system on chip (SOC) package, either in part, orin whole. An SOC represents an IC that integrates components of acomputer or other electronic system into a single chip. It may containdigital, analog, mixed-signal, and converter functions (or some otherdesired functions): all of which may be provided on a single chipsubstrate. Other embodiments may include a multi-chip-module (MCM), witha plurality of separate ICs located within a single electronic packageand configured to interact closely with each other through theelectronic package.

In certain contexts, the features discussed herein can be applicable toconverters being used in many different applications. The featuresherein are also applicable to other signal processing systems that canbe assisted by specialized digital circuitry and/or an on-chip uP.Various exemplary applications include medical systems, scientificinstrumentation, transportation systems, aerospace systems, wireless andwired communications, radar, industrial process control, audio and videoequipment, consumer devices, and other converter-based systems.

In the discussions of the embodiments above, the capacitors, clocks,DFFs, dividers, inductors, resistors, amplifiers, switches, digitalcore, transistors, and/or other components can readily be replaced,substituted, or otherwise modified in order to accommodate particularcircuitry needs. Moreover, it should be noted that the use ofcomplementary electronic devices, hardware, software, etc. offer anequally viable option for implementing the teachings of the presentdisclosure.

Parts of various apparatuses for providing digitally assisted functioncan include electronic circuitry to perform the functions describedherein. In some cases, one or more parts of the apparatus can beprovided by an on-chip uP specially configured for carrying out thefunctions described herein. For instance, the on-chip uP may include oneor more application specific components, or may include programmablelogic gates which are configured to carry out the functions describeherein. The circuitry can operate in analog domain, digital domain, orin a mixed signal domain (but preferably in the digital domain). In someinstances, the processor may be configured to carrying out the functionsdescribed herein by executing one or more instructions stored on anon-transitory computer medium accessible by the on-chip uP.

In one example embodiment, the chip providing the converter and theon-chip uP may be provided on a board of an associated electronicdevice. The board can be a general circuit board that can hold variouscomponents of the internal electronic system of the electronic deviceand, further, provide connectors for other peripherals. For instance,the chip having the converter and the on-chip uP can communicate withthe components of the associated electronic device (e.g., signalgenerators, processors, memory, transmitters, receivers, etc.) Morespecifically, the board can provide the electrical connections by whichthe other components of the system can communicate electrically. Anysuitable processors (inclusive of digital signal processors,microprocessors, supporting chipsets, etc.), computer-readablenon-transitory memory elements, etc. can be suitably coupled to theboard based on particular configuration needs, processing demands,computer designs, etc. Other components such as external storage,additional sensors, controllers for audio/video display, and peripheraldevices may be attached to the board as plug-in cards, via cables, orintegrated into the board itself.

It is also imperative to note that all of the specifications,dimensions, and relationships outlined herein (e.g., the number ofprocessors, logic operations, etc.) have only been offered for purposesof example and teaching only. Such information may be variedconsiderably without departing from the spirit of the presentdisclosure, or the scope of the examples and appended claims. Thespecifications apply only to one non-limiting example and, accordingly,they should be construed as such. In the foregoing description, exampleembodiments have been described with reference to particular processorand/or component arrangements. Various modifications and changes may bemade to such embodiments without departing from the scope of theexamples and appended claims. The description and drawings are,accordingly, to be regarded in an illustrative rather than in arestrictive sense.

Note that with the numerous examples provided herein, interaction may bedescribed in terms of two, three, four, or more electrical components.However, this has been done for purposes of clarity and example only. Itshould be appreciated that the system can be consolidated in anysuitable manner. Along similar design alternatives, any of theillustrated components, modules, and elements of the FIGURES may becombined in various possible configurations, all of which are clearlywithin the broad scope of this Specification. In certain cases, it maybe easier to describe one or more of the functionalities of a given setof flows by only referencing a limited number of electrical elements. Itshould be appreciated that the electrical circuits of the FIGURES andits teachings are readily scalable and can accommodate a large number ofcomponents, as well as more complicated/sophisticated arrangements andconfigurations. Accordingly, the examples provided should not limit thescope or inhibit the broad teachings of the electrical circuits aspotentially applied to a myriad of other architectures.

Note that in this Specification, references to various features (e.g.,elements, structures, modules, components, steps, operations,characteristics, etc.) included in “one embodiment”, “exampleembodiment”, “an embodiment”, “another embodiment”, “some embodiments”,“various embodiments”, “other embodiments”, “alternative embodiment”,and the like are intended to mean that any such features are included inone or more embodiments of the present disclosure, but may or may notnecessarily be combined in the same embodiments.

It is also important to note that the digitally assisted functions,illustrate only some of the possible functions that may be executed by,or within, systems (e.g., specialized digital circuitry and/or on-chipuP) illustrated in the FIGURES. Some of these operations may be deletedor removed where appropriate, or these operations may be modified orchanged considerably without departing from the scope of the presentdisclosure. In addition, the timing of these operations may be alteredconsiderably. The preceding operational flows have been offered forpurposes of example and discussion. Substantial flexibility is providedby embodiments described herein in that any suitable arrangements,chronologies, configurations, and timing mechanisms may be providedwithout departing from the teachings of the present disclosure.

Numerous other changes, substitutions, variations, alterations, andmodifications may be ascertained to one skilled in the art and it isintended that the present disclosure encompass all such changes,substitutions, variations, alterations, and modifications as fallingwithin the scope of the examples and appended claims. Note that alloptional features of the apparatus described above may also beimplemented with respect to the method or process described herein andspecifics in the examples may be used anywhere in one or moreembodiments.

What is claimed is:
 1. A randomized interleaved analog-to-digitalconverter comprising: two or more analog-to-digital converters tosample, interleaved in time according to a pseudo-randomized sequence,an analog input of the randomized interleaved analog-to-digitalconverter and generate respective digital outputs; a digital combiner tocombine the respective digital outputs of the two or moreanalog-to-digital converters to generate a digital output of therandomized interleaved analog-to-digital converter based on thepseudo-randomized sequence; a reference analog-to-digital converter forrandomly sampling the analog input and generating reference digitaloutputs that are representative of the digital outputs of the two ormore analog-to-digital converters based on randomized sampling periods;and calibration logic for measuring interleaving errors of the two-oranalog-to-digital converters based on the respective digital outputs ofthe two-or more analog-to-digital converters and the reference digitaloutputs.
 2. The randomized interleaved analog-to-digital converter ofclaim 1, wherein each time the reference analog-to-digital convertersamples the analog input, the reference analog-to-digital convertersamples the analog-input along with one of the analog-to-digitalconverters that is sampling the analog input.
 3. The randomizedinterleaved analog-to-digital converter of claim 1, wherein thereference analog-to-digital converter has as sampling frequency which isspread out across a range of frequencies.
 4. The randomized interleavedanalog-to-digital converter of claim 1, further comprising: a clockgenerator for generating a clock signal having a range of clock periodsfor the reference analog-to-digital converter to randomly sample theanalog input.
 5. The randomized interleaved analog-to-digital converterof claim 1, further comprising: one or more clock divider circuits thatoutput an edge of a clock signal for driving the referenceanalog-to-digital converter to sample the analog input every X number ofclock cycles of an input clock; and a randomization engine to randomizeX used by the one or more clock divider circuits.
 6. The randomizedinterleaved analog-to-digital converter of claim 1, wherein: a firstresolution of any one of the two or more analog-to-digital converters ishigher than a second resolution of the reference analog-to-digitalconverter.
 7. The randomized interleaved analog-to-digital converter ofclaim 1, wherein the reference analog-to-digital converter serves as anadditional signal path for converting the analog input signal inparallel with the two or more analog-to-digital converters.
 8. A methodfor calibrating a randomized interleaved analog-to-digital convertercomprising: generating, by a clock generator, first clock signals forcontrolling two or more analog-to-digital converters of the randomizedtime-interleaved analog-to-digital converter to sample, interleaved intime according to a pseudo-randomized sequence, an analog input of therandomized time-interleaved analog-to-digital converter; generating, bythe clock generator, a second clock signal for triggering a referenceanalog-to-digital converter to randomly sample the analog input andgenerate digital outputs at randomized periods, wherein, when thereference analog-to-digital converter samples the analog input, one ofthe two or more analog-to-digital converters is also sampling the analoginput at substantially the same time; processing respective digitaloutputs of the two or more analog-to-digital converters and the digitaloutputs of the reference analog-to-digital converter over a period oftime to generate measurements; and determining interleaving errorsassociated with the two or more analog-to-digital converters based onthe measurements.
 9. The method of claim 8, wherein processingrespective digital outputs of the two or more analog-to-digitalconverters and digital outputs of the reference analog-to-digitalconverter to generate measurements comprises: for each one of the two ormore analog-to-digital converters, determining a mean of differencesbetween digital outputs of a particular analog-to-digital converter andcorresponding digital outputs of the reference analog-to-digitalconverter generated when the reference analog-to-digital converter issampling along the particular analog-to-digital converter.
 10. Themethod of claim 9, wherein determining interleaving errors comprisesupdating an offset correction term for the particular analog-to-digitalconverter based on the mean.
 11. The method of claim 8, whereinprocessing respective digital outputs of the two or moreanalog-to-digital converters and digital outputs of the referenceanalog-to-digital converter to generate measurements comprises: for eachone of the two or more analog-to-digital converters, determining a meanof differences between magnitudes of digital outputs of a particularanalog-to-digital converter and magnitudes of corresponding digitaloutputs of the reference analog-to-digital converter generated when thereference analog-to-digital converter is sampling along the particularanalog-to-digital converter.
 12. The method of claim 11, whereindetermining interleaving errors comprises updating an interleaving gaincorrection term for the particular analog-to-digital converter based onthe mean.
 13. The method of claim 8, wherein processing respectivedigital outputs of the two or more analog-to-digital converters anddigital outputs of the reference analog-to-digital converter over aperiod of time to generate measurements comprises: for each one of thetwo or more analog-to-digital converters, determining a crosscorrelation of a first signal representing digital outputs of aparticular analog-to-digital converter and a second signal representingdigital outputs of the reference analog-to-digital converter generatedwhen the reference analog-to-digital converter is sampling along theparticular analog-to-digital converter.
 14. The method of claim 13,wherein determining interleaving errors comprises updating aninterleaving skew correction term for the particular analog-to-digitalconverter based on the cross correlation of the first signal and thesecond signal.
 15. The method of claim 13, wherein the digital outputsof the particular analog-to-digital converter and the digital outputs ofthe reference analog-to-digital converter are represented by a singlebit.
 16. A randomized converter system on a single chip for convertingan analog input to a digital output, the system comprising: two or moreanalog-to-digital converters to sample, interleaved in time according toa pseudo-randomized sequence, the analog input of the randomizedconverter system and generate respective digital outputs; a referenceanalog-to-digital converter for sampling the analog input along with oneof the two or more analog-to-digital converters at random and generatingreference digital outputs according to randomized sampling periods; andlogic for recording measurements of digital outputs of the two or moreanalog-to-digital converters and the reference digital outputs of thereference analog-to-digital converter; and an microprocessor on-chipwith the two or more analog-to-digital converters for assisting therandomized converter system based on the measurements.
 17. Therandomized converter system of claim 16, further comprising: a clockgenerator for generating clock signals to the two or moreanalog-to-digital converters to sample, interleaved in time according tothe pseudo-randomized sequence, and a clock signal to the referenceanalog-to-digital converter for randomly sampling the analog input. 18.The randomized converter system of claim 17, wherein the clock generatorfurther generates a spread spectrum clock signal for clocking theon-chip microprocessor, wherein instantaneous period of the spreadspectrum clock signal is randomized.
 19. The randomized converter systemof claim 16, wherein the on-chip microprocessor executes instructionsfor computing one or more of the following: interleaving offsetcorrection term, interleaving gain correction term, interleaving skewcorrection term, frequency response, and linearity of any one of the twoor more analog -to-digital converters.
 20. The randomized convertersystem of claim 16, wherein the reference analog-to-digital converterand the two or more analog-to-digital converters are each sampling theanalog input according to randomized periods.